Sample records for gene expression technique

We prepared probes for isolating functional pieces of the metallothionein locus. The probes enabled a variety of experiments, eventually revealing two mechanisms for metallothionein geneexpression, the order of the DNA coding units at the locus, and the location of the gene site in its chromosome. Once the switch regulating metallothionein synthesis was located, it could be joined by recombinant DNA methods to other, unrelated genes, then reintroduced into cells by gene-transfer techniques. The expression of these recombinant genes could then be induced by exposing the cells to Zn 2+ or Cd 2+ . We would thus take advantage of the clearly defined switching properties of the metallothionein gene to manipulate the expression of other, perhaps normally constitutive, genes. Already, despite an incomplete understanding of how the regulatory switch of the metallothionein locus operates, such experiments have been performed successfully

The response to any radiation accident or incident involving actual or potential ionising radiation exposure requires accurate and rapid assessment of the doses received by individuals. The techniques available today for biodosimetry purposes are not fully adapted to rapid high-throughput measurements of exposures in large numbers of individuals. A recently emerging technique is based on geneexpression analysis, as there are a number of genes which are radiation responsive in a dose-dependent manner. The present work aimed to assess a new technique which allows the detection of the level of expression of up to 800 genes without need of enzymatic reactions. In order to do so, human peripheral blood was exposed ex vivo to a range of x-ray doses from 5 mGy to 4 Gy of x-rays and the transcriptional expression of five radiation-responsive genes PHPT1, PUMA, CCNG1, DDB2 and MDM2 was studied by both the nCounter Digital Analyzer and Multiplex Quantitative Real-Time Polymerase Chain Reaction (MQRT-PCR) as the benchmark technology. Results from both techniques showed good correlation for all genes with R{sup 2} values ranging between 0.8160 and 0.9754. The reproducibility of the nCounter Digital Analyzer was also assessed in independent biological replicates and proved to be good. Although the slopes of the correlation of results obtained by the techniques suggest that MQRT-PCR is more sensitive than the nCounter Digital Analyzer, the nCounter Digital Analyzer provides sensitive and reliable data on modifications in geneexpression in human blood exposed to radiation without enzymatic amplification of RNA prior to analysis.

In vitro mutagenesis on Dendrobium Sonia in MINT has produced mutants with wide range of flower form and colour variations. Among the mutants are plants with different flower size and shape. These changes could be caused by alterations to the expression level of the genes responsible for the characteristics. In this studies, Differential Display technique was used to identify and analyse altered geneexpression at the mRNA level. Total RNA of the control and mutants were reversed transcribed using three anchored oligo-d T primers. Subsequently, these cDNAs were Pcr amplified in combination with 16 arbitrary primers. The amplified products were electrophoresed side by side on agarose gel. Differentially expressed bands are isolated for further analysis. (Author)

The fast growing field of molecular imaging has achieved major advances in imaging geneexpression, an important element of gene therapy. Geneexpression imaging is based on specific probes or contrast agents that allow either direct or indirect spatio-temporal evaluation of geneexpression. Direct evaluation is possible with, for example, contrast agents that bind directly to a specific target (e.g., receptor). Indirect evaluation may be achieved by using specific substrate probes for a target enzyme. The use of marker genes, also called reporter genes, is an essential element of MI approaches for geneexpression in gene therapy. The marker gene may not have a therapeutic role itself, but by coupling the marker gene to a therapeutic gene, expression of the marker gene reports on the expression of the therapeutic gene. Nuclear medicine and optical approaches are highly sensitive (detection of probes in the picomolar range), whereas MRI and ultrasound imaging are less sensitive and require amplification techniques and/or accumulation of contrast agents in enlarged contrast particles. Recently developed MI techniques are particularly relevant for gene therapy. Amongst these are the possibility to track gene therapy vectors such as stem cells, and the techniques that allow spatiotemporal control of geneexpression by non-invasive heating (with MRI guided focused ultrasound) and the use of temperature sensitive promoters. (orig.)

Full Text Available Abstract Background The wide use of high-throughput DNA microarray technology provide an increasingly detailed view of human transcriptome from hundreds to thousands of genes. Although biomedical researchers typically design microarray experiments to explore specific biological contexts, the relationships between genes are hard to identified because they are complex and noisy high-dimensional data and are often hindered by low statistical power. The main challenge now is to extract valuable biological information from the colossal amount of data to gain insight into biological processes and the mechanisms of human disease. To overcome the challenge requires mathematical and computational methods that are versatile enough to capture the underlying biological features and simple enough to be applied efficiently to large datasets. Methods Unsupervised machine learning approaches provide new and efficient analysis of geneexpression profiles. In our study, two unsupervised knowledge-based matrix factorization methods, independent component analysis (ICA and nonnegative matrix factorization (NMF are integrated to identify significant genes and related pathways in microarray geneexpression dataset of Alzheimer’s disease. The advantage of these two approaches is they can be performed as a biclustering method by which genes and conditions can be clustered simultaneously. Furthermore, they can group genes into different categories for identifying related diagnostic pathways and regulatory networks. The difference between these two method lies in ICA assume statistical independence of the expression modes, while NMF need positivity constrains to generate localized geneexpression profiles. Results In our work, we performed FastICA and non-smooth NMF methods on DNA microarray geneexpression data of Alzheimer’s disease respectively. The simulation results shows that both of the methods can clearly classify severe AD samples from control samples, and

Full Text Available Background. Many gene-expression signatures exist for describing the biological state of profiled tumors. Principal Component Analysis (PCA can be used to summarize a gene signature into a single score. Our hypothesis is that gene signatures can be validated when applied to new datasets, using inherent properties of PCA. Results. This validation is based on four key concepts. Coherence: elements of a gene signature should be correlated beyond chance. Uniqueness: the general direction of the data being examined can drive most of the observed signal. Robustness: if a gene signature is designed to measure a single biological effect, then this signal should be sufficiently strong and distinct compared to other signals within the signature. Transferability: the derived PCA gene signature score should describe the same biology in the target dataset as it does in the training dataset. Conclusions. The proposed validation procedure ensures that PCA-based gene signatures perform as expected when applied to datasets other than those that the signatures were trained upon. Complex signatures, describing multiple independent biological components, are also easily identified.

Microarray technology can be considered the most powerful tool for screening geneexpression profiles of biological samples. After data mining, results need to be validated with highly reliable biotechniques allowing for precise quantitation of transcriptional abundance of identified genes. Quantitative real time PCR (qrt-PCR) technology has recently reached a level of sensitivity, accuracy and practical ease that support its use as a routine bioinstrumentation for gene level measurement. Currently, qrt-PCR is considered by most experts the most appropriate method to confirm or confute microarray-generated data. The knowledge of the biochemical principles underlying qrt-PCR as well as some related technical issues must be beard in mind when using this biotechnology.

The Qira black sheep and the Hetian sheep are two local breeds in the Northwest of China, which are characterized by high-fecundity and low-fecundity breed respectively. The elucidation of mRNA expression profiles in the ovaries among different sheep breeds representing fecundity extremes will helpful for identification and utilization of major prolificacy genes in sheep. In the present study, we performed RNA-seq technology to compare the difference in ovarian mRNA expression profiles between Qira black sheep and Hetian sheep. From the Qira black sheep and the Hetian sheep libraries, we obtained a total of 11,747,582 and 11,879,968 sequencing reads, respectively. After aligning to the reference sequences, the two libraries included 16,763 and 16,814 genes respectively. A total of 1,252 genes were significantly differentially expressed at Hetian sheep compared with Qira black sheep. Eight differentially expressedgenes were randomly selected for validation by real-time RT-PCR. This study provides a basic data for future research of the sheep reproduction. PMID:25790350

Full Text Available The Qira black sheep and the Hetian sheep are two local breeds in the Northwest of China, which are characterized by high-fecundity and low-fecundity breed respectively. The elucidation of mRNA expression profiles in the ovaries among different sheep breeds representing fecundity extremes will helpful for identification and utilization of major prolificacy genes in sheep. In the present study, we performed RNA-seq technology to compare the difference in ovarian mRNA expression profiles between Qira black sheep and Hetian sheep. From the Qira black sheep and the Hetian sheep libraries, we obtained a total of 11,747,582 and 11,879,968 sequencing reads, respectively. After aligning to the reference sequences, the two libraries included 16,763 and 16,814 genes respectively. A total of 1,252 genes were significantly differentially expressed at Hetian sheep compared with Qira black sheep. Eight differentially expressedgenes were randomly selected for validation by real-time RT-PCR. This study provides a basic data for future research of the sheep reproduction.

The aim of this study was to develop a sensitive in situ hybridization methodology using fluorescence-labeled riboprobes (FISH) that allows for the evaluation of geneexpression profiles simultaneously in multiple target tissues of whole fish sections of Japanese medaka (Oryzias latipes). To date FISH methods have been limited in their application due to autofluorescence of tissues, fixatives or other components of the hybridization procedure. An optimized FISH method, based on confocal fluorescence microscopy was developed to reduce the autofluorescence signal. Because of its tissue- and gender-specific expression and relevance in studies of endocrine disruption, gonadal aromatase (CYP19a) was used as a model gene. The in situ hybridization (ISH) system was validated in a test exposure with the aromatase inhibitor fadrozole. The optimized FISH method revealed tissue-specific expression of the CYP19a gene. Furthermore, the assay could differentiate the abundance of CYP19a mRNA among cell types. Expression of CYP19a was primarily associated with early stage oocytes, and expression gradually decreased with increasing maturation. No expression of CYP19a mRNA was observed in other tissues such as brain, liver, or testes. Fadrozole (100 μg/L) caused up-regulation of CYP19a expression, a trend that was confirmed by RT-PCR analysis on excised tissues. In a combination approach with gonad histology, it could be shown that the increase in CYP19a expression as measured by RT-PCR on a whole tissue basis was due to a combination of both increases in numbers of CYP19a-containing cells and an increase in the amount of CYP19a mRNA present in the cells

Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on 'suicide gene therapy' of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k + ) has been use for 'suicide' in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k + geneexpression where the H S V-1 t k + gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([ 18 F]F H P G; [ 18 F]-A C V), and pyrimidine- ([ 123 / 131 I]I V R F U; [ 124 / 131I ]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [ 123 / 131I ]I V R F U imaging with the H S V-1 t k + reporter gene will be presented

Full text. Gene therapy can be used to introduce new genes, or to supplement the function of indigenous genes. At the present time, however, there is non-invasive test to demonstrate efficacy of the gene transfer and expression processes. It has been postulated that scintigraphic imaging can offer unique information on both the site at which the transferred gene is expressed, and the degree of expression, both of which are critical issue for safety and clinical efficacy. Many current studies are based on `suicide gene therapy` of cancer. Cells modified to express these genes commit metabolic suicide in the presence of an enzyme encoded by the transferred gene and a specifically-convertible pro drug. Pro drug metabolism can lead to selective metabolic trapping, required for scintigraphy. Herpes simplex virus type-1 thymidine kinase (H S V-1 t k{sup +}) has been use for `suicide` in vivo tumor gene therapy. It has been proposed that radiolabelled nucleosides can be used as radiopharmaceuticals to detect H S V-1 t k{sup +} geneexpression where the H S V-1 t k{sup +} gene serves a reporter or therapeutic function. Animal gene therapy models have been studied using purine-([{sup 18} F]F H P G; [{sup 18} F]-A C V), and pyrimidine- ([{sup 123}/{sup 131} I]I V R F U; [{sup 124}/{sup 131I}]) antiviral nucleosides. Principles of gene therapy and gene therapy imaging will be reviewed and experimental data for [{sup 123}/{sup 131I}]I V R F U imaging with the H S V-1 t k{sup +} reporter gene will be presented

This patent describes a method of regulating the expression of a gene in a eucaryotic cell. The method consists of: providing in the eucaryotic cell, a peptide, derived from or substantially similar to a peptide of a procaryotic cell able to bind to DNA upstream from or within the gene, the amount of the peptide being sufficient to bind to the gene and thereby control expression of the gene.

The correct observation/estimation of surface incoming solar radiation (RS) is very important for many agricultural, meteorological and hydrological related applications. While most weather stations are provided with sensors for air temperature detection, the presence of sensors necessary for the detection of solar radiation is not so habitual and the data quality provided by them is sometimes poor. In these cases it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using GeneExpression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). Traditional temperature based solar radiation equations were also included in this study and compared with artificial intelligence based approaches. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SSRMSE), MAE-based skill score (SSMAE) and r2 criterion of Nash and Sutcliffe criteria were used to assess the models' performances. An ANN (a four-input multilayer perceptron with ten neurons in the hidden layer) presented the best performance among the studied models (2.93 MJ m-2 d-1 of RMSE). A four-input ANFIS model revealed as an interesting alternative to ANNs (3.14 MJ m-2 d-1 of RMSE). Very limited number of studies has been done on estimation of solar radiation based on ANFIS, and the present one demonstrated the ability of ANFIS to model solar radiation based on temperatures and extraterrestrial radiation. By the way this study demonstrated, for the first time, the ability of GEP models to model solar radiation based on daily atmospheric variables. Despite the accuracy of GEP models was slightly lower than the ANFIS and ANN models the genetic programming models (i.e., GEP) are superior to other artificial intelligence models in giving a simple explicit equation for the

Full Text Available It has been established that an intricate program of geneexpression controls progression through the different stages in development. The equally complex biological phenomenon known as aging is genetically determined and environmentally modulated. This review focuses on the genetic component of aging, with a special emphasis on differential geneexpression. At least two genetic pathways regulating organism longevity act by modifying geneexpression. Many genes are also subjected to age-dependent transcriptional regulation. Some age-related geneexpression changes are prevented by caloric restriction, the most robust intervention that slows down the aging process. Manipulating the expression of some age-regulated genes can extend an organism's life span. Remarkably, the activity of many transcription regulatory elements is linked to physiological age as opposed to chronological age, indicating that orderly and tightly controlled regulatory pathways are active during aging.

Highlights: ► Solar radiation estimation based on GeneExpression Programming is unexplored. ► This approach is evaluated for the first time in this study. ► Other artificial intelligence models (ANN and ANFIS) are also included in the study. ► New alternatives for solar radiation estimation based on temperatures are provided. - Abstract: Surface incoming solar radiation is a key variable for many agricultural, meteorological and solar energy conversion related applications. In absence of the required meteorological sensors for the detection of global solar radiation it is necessary to estimate this variable. Temperature based modeling procedures are reported in this study for estimating daily incoming solar radiation by using GeneExpression Programming (GEP) for the first time, and other artificial intelligence models such as Artificial Neural Networks (ANNs), and Adaptive Neuro-Fuzzy Inference System (ANFIS). A comparison was also made among these techniques and traditional temperature based global solar radiation estimation equations. Root mean square error (RMSE), mean absolute error (MAE) RMSE-based skill score (SS RMSE ), MAE-based skill score (SS MAE ) and r 2 criterion of Nash and Sutcliffe criteria were used to assess the models’ performances. An ANN (a four-input multilayer perceptron with 10 neurons in the hidden layer) presented the best performance among the studied models (2.93 MJ m −2 d −1 of RMSE). The ability of GEP approach to model global solar radiation based on daily atmospheric variables was found to be satisfactory.

Understanding molecular alterations in colorectal cancer (CRC) is needed to define new biomarkers and treatment targets. We used oligonucleotide microarrays to monitor geneexpression of about 6,800 known genes and 35,000 expressed sequence tags (ESTs) on five pools (four to six samples in each...... pool) of total RNA from left-sided sporadic colorectal carcinomas. We compared normal tissue to carcinoma tissue from Dukes' stages A-D (noninvasive to distant metastasis) and identified 908 known genes and 4,155 ESTs that changed remarkably from normal to tumor tissue. Based on intensive filtering 226...

This report investigates for the first time the potential inter-treatment bias source of cell number for geneexpression studies. Cell-number bias can affect geneexpression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies....... For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce...

The Transgenic Arabidopsis GeneExpression System (TAGES) investigation is one in a pair of investigations that use the Advanced Biological Research System (ABRS) facility. TAGES uses Arabidopsis thaliana, thale cress, with sensor promoter-reporter gene constructs that render the plants as biomonitors (an organism used to determine the quality of the surrounding environment) of their environment using real-time nondestructive Green Fluorescent Protein (GFP) imagery and traditional postflight analyses.

To determine the role of tissue differentiation on expression of each of the papillomavirus mRNA species identified by electron microscopy, the authors prepared exon-specific RNA probes that could distinguish the alternatively spliced mRNA species. Radioactively labeled single-stranded RNA probes were generated from a dual promoter vector system and individually hybridized to adjacent serial sections of formalin-fixed, paraffin-embedded biopsies of condylomata. Autoradiography showed that each of the message species had a characteristic tissue distribution and relative abundance. The authors have characterized a portion of the regulatory network of the HPVs by showing that the E2 ORF encodes a trans-acting enhancer-stimulating protein, as it does in BPV-1 (Spalholz et al. 1985). The HPV-11 enhancer was mapped to a 150-bp tract near the 3' end of the URR. Portions of this region are duplicated in some aggressive strains of HPV-6 (Boshart and zur Hausen 1986; Rando et al. 1986). To test the possible biological relevance of these duplications, they cloned tandem arrays of the enhancer and demonstrated, using a chloramphenicol acetyltransferase (CAT) assay, that they led to dramatically increased transcription proportional to copy number. Using the CAT assays, the authors found that the E2 proteins of several papillomavirus types can cross-stimulate the enhancers of most other types. This suggests that prior infection of a tissue with one papillomavirus type may provide a helper effect for superinfection and might account fo the HPV-6/HPV-16 coinfections in condylomata that they have observed

(ectoderm) specification with co-opted functions in notochord formation in chordates and left/right determination in ambulacrarians and vertebrates. The caudal ortholog, TtrCdx, is first expressed in the ectoderm of the gastrulating embryo in the posterior region of the blastopore. Its expression stays......The molecular control that underlies brachiopod ontogeny is largely unknown. In order to contribute to this issue we analyzed the expression pattern of two homeobox containing genes, Not and Cdx, during development of the rhynchonelliform (i.e., articulate) brachiopod Terebratalia transversa...... completion of larval development, which is marked by a three-lobed body with larval setae. Expression starts at gastrulation in two areas lateral to the blastopore and subsequently extends over the animal pole of the gastrula. With elongation of the gastrula, expression at the animal pole narrows to a small...

Full Text Available The phloem is the conduit through which photoassimilates are distributed from autotrophic to heterotrophic tissues and is involved in the distribution of signaling molecules that coordinate plant growth and responses to the environment. Phloem function depends on the coordinate expression of a large array of genes. We have previously identified conserved motifs in upstream regions of the Arabidopsis genes, encoding the homologs of pumpkin phloem sap mRNAs, displaying expression in vascular tissues. This tissue-specific expression in Arabidopsis is predicted by the overrepresentation of GA/CT-rich motifs in gene promoters. In this work we have searched for common motifs in upstream regions of the homologous genes from plants considered to possess a primitive vascular tissue (a lycophyte, as well as from others that lack a true vascular tissue (a bryophyte, and finally from chlorophytes. Both lycophyte and bryophyte display motifs similar to those found in Arabidopsis with a significantly low E-value, while the chlorophytes showed either a different conserved motif or no conserved motif at all. These results suggest that these same genes are expressed coordinately in non- vascular plants; this coordinate expression may have been one of the prerequisites for the development of conducting tissues in plants. We have also analyzed the phylogeny of conserved proteins that may be involved in phloem function and development. The presence of CmPP16, APL, FT and YDA in chlorophytes suggests the recruitment of ancient regulatory networks for the development of the vascular tissue during evolution while OPS is a novel protein specific to vascular plants.

A large number of proteins are specifically synthesized in the hepatocyte. Only the adult liver expresses the complete repertoire of functions which are required at various stages during development. There is therefore a complex series of regulatory mechanisms responsible for the maintenance of the differentiated state and for the developmental and physiological variations in the pattern of geneexpression. Human hepatoma cell lines HepG2 and Hep3B display a pattern of geneexpression similar to adult and fetal liver, respectively; in contrast, cultured fibroblasts or HeLa cells do not express most of the liver specific genes. They have used these cell lines for transfection experiments with cloned human liver specific genes. DNA segments coding for alpha1-antitrypsin and retinol binding protein (two proteins synthesized both in fetal and adult liver) are expressed in the hepatoma cell lines HepG2 and Hep3B, but not in HeLa cells or fibroblasts. A DNA segment coding for haptoglobin (a protein synthesized only after birth) is only expressed in the hepatoma cell line HepG2 but not in Hep3B nor in non hepatic cell lines. The information for tissue specific expression is located in the 5' flanking region of all three genes. In vivo competition experiments show that these DNA segments bind to a common, apparently limiting, transacting factor. Conventional techniques (Bal deletions, site directed mutagenesis, etc.) have been used to precisely identify the DNA sequences responsible for these effects. The emerging picture is complex: they have identified multiple, separate transcriptional signals, essential for maximal promoter activation and tissue specific expression. Some of these signals show a negative effect on transcription in fibroblast cell lines.

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in geneexpression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is geneexpression evolution autonomous? To address this here we consider evolution of human geneexpression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in geneexpression of a focal gene on average predicts the change in geneexpression of neighbors. The effect is highly pronounced in the immediate vicinity (genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of geneexpression, a change in geneexpression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

The cost, prevalence and pain associated with endodontic disease necessitate an understanding of the fundamental molecular aspects of its pathogenesis. This study was aimed to identify the genetic contributors to pulpal pain and inflammation. Inflamed pulps were collected from patients diagnosed with irreversible pulpitis (n=20). Normal pulps from teeth extracted for various reasons served as controls (n=20). Pain level was assessed using a visual analog scale (VAS). Genome-wide microarray analysis was performed using Affymetrix GeneTitan Multichannel Instrument. The difference in geneexpression levels were determined by the significance analysis of microarray program using a false discovery rate (q-value) of 5%. Genes involved in immune response, cytokine-cytokine receptor interaction and signaling, integrin cell surface interactions, and others were expressed at relatively higher levels in the pulpitis group. Moreover, several genes known to modulate pain and inflammation showed differential expression in asymptomatic and mild pain patients (⩾30 mm on VAS) compared with those with moderate to severe pain. This exploratory study provides a molecular basis for the clinical diagnosis of pulpitis. With an enhanced understanding of pulpal inflammation, future studies on treatment and management of pulpitis and on pain associated with it can have a biological reference to bridge treatment strategies with pulpal biology.

The use of geneexpression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in geneexpression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline geneexpression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

Phenotypic variation is ubiquitous in biology and is often traceable to underlying genetic and environmental variation. However, even genetically identical cells in identical environments display variable phenotypes. Stochastic geneexpression, or geneexpression "noise," has been suggested as a

Recently, experiments on mRNA abundance (geneexpression) have revealed that geneexpression shows a stationary organization described by a scale-free distribution. Here we propose a constructive approach to geneexpression dynamics which restores the scale-free exponent and describes the intermediate state dynamics. This approach requires only one assumption: Markov property

The responses to ionizing radiation are complex and are regulated by a number of overlapping molecular pathways. One such stress-signaling pathway involves p53, which regulates the expression of over 100 genes already identified. It is also becoming increasingly apparent that the pattern of stress geneexpression has some cell type specificity. It may be possible to exploit these differences in stress gene responsiveness as molecular markers through the use of a combined informatics and functional genomic approach. The techniques of micro-array analysis potentially offer the opportunity to monitor changes in geneexpression across the entire set of expressedgenes in a cell or organism. It again highlights the importance of a cellular context to genotoxic stress responses; it also raises the prospect of expression profiling of cell lines, tissues, and tumors. Such profiles may have a predictive value in cancer therapy regimens, or identification of exposures to environmental toxins

A new approach for modulating geneexpression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...... that the method can be applied to modulating the expression of native genes on the chromosome. We constructed a series of strains in which the expression of the las operon, containing the genes pfk, pyk, and ldh, was modulated by integrating a truncated copy of the pfk gene. Importantly, the modulation affected...

knockout and strong overexpression. However, applications such as metabolic optimization and control analysis necessitate a continuous set of expression levels with only slight increments in strength to cover a specific window around the wildtype expression level of the studied gene; this requirement can......The study of gene function often requires changing the expression of a gene and evaluating the consequences. In principle, the expression of any given gene can be modulated in a quasi-continuum of discrete expression levels but the traditional approaches are usually limited to two extremes: gene...

Full Text Available Geneexpression levels are important quantitative traits that link genotypes to molecular functions and fitness. In Drosophila, population-genetic studies have revealed substantial adaptive evolution at the genomic level, but the evolutionary modes of geneexpression remain controversial. Here, we present evidence that adaptation dominates the evolution of geneexpression levels in flies. We show that 64% of the observed expression divergence across seven Drosophila species are adaptive changes driven by directional selection. Our results are derived from time-resolved data of geneexpression divergence across a family of related species, using a probabilistic inference method for gene-specific selection. Adaptive geneexpression is stronger in specific functional classes, including regulation, sensory perception, sexual behavior, and morphology. Moreover, we identify a large group of genes with sex-specific adaptation of expression, which predominantly occurs in males. Our analysis opens an avenue to map system-wide selection on molecular quantitative traits independently of their genetic basis.

We present a technique to characterize differentially expressedgenes in terms of their position in a high-dimensional co-expression network. The set-up of Gaussian graphical models is used to construct representations of the co-expression network in such a way that redundancy and the propagation...... that allow to make effective inference in problems with high degree of complexity (e.g. several thousands of genes) and small number of observations (e.g. 10-100) as typically occurs in high throughput geneexpression studies. Taking advantage of the internal structure of decomposable graphical models, we...... construct a compact representation of the co-expression network that allows to identify the regions with high concentration of differentially expressedgenes. It is argued that differentially expressedgenes located in highly interconnected regions of the co-expression network are less informative than...

Full Text Available Comprehensive geneexpression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressedgenes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressedgenes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive geneexpression data.

Comprehensive geneexpression analysis using DNA microarrays has become a widespread technique in molecular biological research. In the biomaterials field, it is used to evaluate the biocompatibility or cellular toxicity of metals, polymers and ceramics. Studies in this field have extracted differentially expressedgenes in the context of differences in cellular responses among multiple materials. Based on these genes, the effects of materials on cells at the molecular level have been examined. Expression data ranging from several to tens of thousands of genes can be obtained from DNA microarrays. For this reason, several tens or hundreds of differentially expressedgenes are often present in different materials. In this review, we outline the principles of DNA microarrays, and provide an introduction to methods of extracting information which is useful for evaluating and designing biomaterials from comprehensive geneexpression data. (topical review)

Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell geneexpression assays (single cell qPCR and RNA-seq). These experimental approaches generate geneexpression distributions which can be used to estimate the kinetic parameters of geneexpression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete ...

The evolution of a gene’s expression profile is commonly assumed to be independent of its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between expression of neighboring genes in extant taxa. Indeed, in all eukaryotic genomes, genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their e...

Candida albicans is one of the most common fungal pathogen in humans due to its high frequency as an opportunistic and pathogenic fungus causing superficial as well as invasive infections in immunocompromised patients. An understanding of gene function in C. albicans is necessary to study the molecular basis of its pathogenesis, virulence and drug resistance. Several manipulation techniques have been used for investigation of gene function in C. albicans, including gene disruption, controlled geneexpression, protein tagging, gene reintegration, and overexpression. In this review, the main cassettes containing selectable markers used for gene manipulation in C. albicans are summarized; the advantages and limitations of these cassettes are discussed concerning the influences on the target geneexpression and the virulence of the mutant strains.

We used scaled factorial moments to search for intermittency in the log expression ratios (LERs) for thousands of genes spotted on cDNA microarrays (gene chips). Results indicate varying levels of intermittency in geneexpression. The observation of intermittency in the data analyzed provides a complimentary handle on moderately expressedgenes, generally not tackled by conventional techniques.

The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

The present invention relates to methods for monitoring differential expression of a plurality of genes in a first filamentous fungal cell relative to expression of the same genes in one or more second filamentous fungal cells using microarrays containing Trichoderma reesei ESTs or SSH clones, or a combination thereof. The present invention also relates to computer readable media and substrates containing such array features for monitoring expression of a plurality of genes in filamentous fungal cells.

Full Text Available Abstract Background Sequence and transcriptional variability within and between individuals are typically studied independently. The joint analysis of sequence and geneexpression variation (genetical genomics provides insight into the role of linked sequence variation in the regulation of geneexpression. We investigated the role of sequence variation in cis on geneexpression (cis sequence effects in a group of genes commonly studied in cancer research in lymphoblastoid cell lines. We estimated the proportion of genes exhibiting cis sequence effects and the proportion of geneexpression variation explained by cis sequence effects using three different analytical approaches, and compared our results to the literature. Results We generated geneexpression profiling data at N = 697 candidate genes from N = 30 lymphoblastoid cell lines for this study and used available candidate gene resequencing data at N = 552 candidate genes to identify N = 30 candidate genes with sufficient variance in both datasets for the investigation of cis sequence effects. We used two additive models and the haplotype phylogeny scanning approach of Templeton (Tree Scanning to evaluate association between individual SNPs, all SNPs at a gene, and diplotypes, with log-transformed geneexpression. SNPs and diplotypes at eight candidate genes exhibited statistically significant (p cis sequence effects in our study, respectively. Conclusion Based on analysis of our results and the extant literature, one in four genes exhibits significant cis sequence effects, and for these genes, about 30% of geneexpression variation is accounted for by cis sequence variation. Despite diverse experimental approaches, the presence or absence of significant cis sequence effects is largely supported by previously published studies.

Abstract Background MicroRNAs (miRNAs) are non-coding RNAs that regulate geneexpression by binding to the messenger RNA (mRNA) of protein coding genes. They control geneexpression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA geneexpression microarray data to predict miRNAs associated with particular diseases or conditions. Results Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in geneexpression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with geneexpression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. Conclusions We describe a technique to integrate geneexpression data and miRNA target predictions from multiple sources.

BACKGROUND: MicroRNAs (miRNAs) are non-coding RNAs that regulate geneexpression by binding to the messenger RNA (mRNA) of protein coding genes. They control geneexpression by either inhibiting translation or inducing mRNA degradation. A number of computational techniques have been developed to identify the targets of miRNAs. In this study we used predicted miRNA-gene interactions to analyse mRNA geneexpression microarray data to predict miRNAs associated with particular diseases or conditions. RESULTS: Here we combine correspondence analysis, between group analysis and co-inertia analysis (CIA) to determine which miRNAs are associated with differences in geneexpression levels in microarray data sets. Using a database of miRNA target predictions from TargetScan, TargetScanS, PicTar4way PicTar5way, and miRanda and combining these data with geneexpression levels from sets of microarrays, this method produces a ranked list of miRNAs associated with a specified split in samples. We applied this to three different microarray datasets, a papillary thyroid carcinoma dataset, an in-house dataset of lipopolysaccharide treated mouse macrophages, and a multi-tissue dataset. In each case we were able to identified miRNAs of biological importance. CONCLUSIONS: We describe a technique to integrate geneexpression data and miRNA target predictions from multiple sources.

weight maintenance diets. For 175 genes, opposite regulation was observed during calorie restriction and weight maintenance phases, independently of variations in body weight. Metabolism and immunity genes showed inverse profiles. During the dietary intervention, network-based analyses revealed strong...... interconnection between expression of genes involved in de novo lipogenesis and components of the metabolic syndrome. Sex had a marked influence on AT expression of 88 transcripts, which persisted during the entire dietary intervention and after control for fat mass. In women, the influence of body mass index...... on expression of a subset of genes persisted during the dietary intervention. Twenty-two genes revealed a metabolic syndrome signature common to men and women. Genetic control of AT geneexpression by cis signals was observed for 46 genes. Dietary intervention, sex, and cis genetic variants independently...

Full Text Available This paper presents how buy and sell trading rules are generated using geneexpression programming with special setup. Market concepts are presented and market analysis is discussed with emphasis on technical analysis and quantitative methods. The use of genetic algorithms in deriving trading rules is presented. Geneexpression programming is applied in a form where multiple types of operators and operands are used. This gives birth to multiple gene contexts and references between genes in order to keep the linear structure of the geneexpression programming chromosome. The setup of multiple gene contexts is presented. The case study shows how to use the proposed gene setup to derive trading rules encoded by Boolean expressions, using a dataset with the reference exchange rates between the Euro and the Romanian leu. The conclusions highlight the positive results obtained in deriving useful trading rules.

Genome mining approaches predict dozens of biosynthetic gene clusters in each of the filamentous fungal genomes sequenced so far. However, the majority of these gene clusters still remain cryptic because they are not expressed in their natural host. Simultaneous expression of all genes belonging to a biosynthetic pathway in a heterologous host is one approach to activate biosynthetic gene clusters and to screen the metabolites produced for bioactivities. Polycistronic expression of all pathway genes under control of a single and tunable promoter would be the method of choice, as this does not only simplify cloning procedures, but also offers control on timing and strength of expression. However, polycistronic geneexpression is a feature not commonly found in eukaryotic host systems, such as Aspergillus niger. In this study, we tested the suitability of the viral P2A peptide for co-expression of three genes in A. niger. Two genes descend from Fusarium oxysporum and are essential to produce the secondary metabolite enniatin (esyn1, ekivR). The third gene (luc) encodes the reporter luciferase which was included to study position effects. Expression of the polycistronic gene cassette was put under control of the Tet-On system to ensure tunable geneexpression in A. niger. In total, three polycistronic expression cassettes which differed in the position of luc were constructed and targeted to the pyrG locus in A. niger. This allowed direct comparison of the luciferase activity based on the position of the luciferase gene. Doxycycline-mediated induction of the Tet-On expression cassettes resulted in the production of one long polycistronic mRNA as proven by Northern analyses, and ensured comparable production of enniatin in all three strains. Notably, gene position within the polycistronic expression cassette matters, as, luciferase activity was lowest at position one and had a comparable activity at positions two and three. The P2A peptide can be used to express at

Based on previously developed solid-phase gene extraction (SPGE) we examined the mRNA profile in primary roots of Brassica rapa seedlings for highly expressedgenes like ACT7 (actin7), TUB (tubulin1), UBQ (ubiquitin), and low expressed GLK (glucokinase) during the first day post-germination. The assessment was based on the mRNA load of the SPGE probe of about 2.1 ng. The number of copies of the investigated genes changed spatially along the length of primary roots. The expression level of all genes differed significantly at each sample position. Among the examined genes ACT7 expression was most even along the root. UBQ was highest at the tip and root-shoot junction (RS). TUB and GLK showed a basipetal gradient. The temporal expression of UBQ was highest in the MZ 9 h after primary root emergence and higher than at any other sample position. Expressions of GLK in EZ and RS increased gradually over time. SPGE extraction is the result of oligo-dT and oligo-dA hybridization and the results illustrate that SPGE can be used for geneexpression profiling at high spatial and temporal resolution. SPGE needles can be used within two weeks when stored at 4 °C. Our data indicate that geneexpression studies that are based on the entire root miss important differences in geneexpression that SPGE is able to resolve for example growth adjustments during gravitropism.

The processes occurring in climatic change evolution and their variations play a major role in environmental engineering. Different techniques are used to model the relationship between temperatures, dew point and relative humidity. Geneexpression programming is capable of modelling complex realities with great accuracy, allowing, at the same time, the extraction of knowledge from the evolved models compared to other learning algorithms. This research aims to use GeneExpression Programming ...

Technological developments and intense research over the last years have led to a better understanding of the 3D structure of the genome and its influence on genome function inside the cell nucleus. We will summarize topological studies performed on four model gene loci: the alpha- and beta-globin

In 1995, serial analysis of geneexpression (SAGE) was developed as a versatile tool for geneexpression studies. SAGE technology does not require pre-existing knowledge of the genome that is being examined and therefore SAGE can be applied to many different model systems. In this chapter, the SAGE

Members of the Sox gene family play roles in many biological processes including organogenesis. We carried out comparative in situ hybridization analysis of seventeen sox genes (Sox1-14, 17, 18, 21) during murine odontogenesis from the epithelial thickening to the cytodifferentiation stages. Localized expression of five Sox genes (Sox6, 9, 13, 14 and 21) was observed in tooth bud epithelium. Sox13 showed restricted expression in the primary enamel knots. At the early bell stage, three Sox genes (Sox8, 11, 17 and 21) were expressed in pre-ameloblasts, whereas two others (Sox5 and 18) showed expression in odontoblasts. Sox genes thus showed a dynamic spatio-temporal expression during tooth development.

Full Text Available Gene co-expression network analysis has been shown effective in identifying functional co-expressedgene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG has been applied to many real-world data sets such as financial stock prices and geneexpression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3, the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA by: i introducing quality control of co-expression similarities, ii parallelizing embedded network construction, and iii developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs. We applied MEGENA to a series of simulated data and the geneexpression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA. MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressedgene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

Gene co-expression network analysis has been shown effective in identifying functional co-expressedgene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a graph filtering technique called Planar Maximally Filtered Graph (PMFG) has been applied to many real-world data sets such as financial stock prices and geneexpression to extract meaningful and relevant interactions. However, PMFG is not suitable for large-scale genomic data due to several drawbacks, such as the high computation complexity O(|V|3), the presence of false-positives due to the maximal planarity constraint, and the inadequacy of the clustering framework. Here, we developed a new co-expression network analysis framework called Multiscale Embedded Gene Co-expression Network Analysis (MEGENA) by: i) introducing quality control of co-expression similarities, ii) parallelizing embedded network construction, and iii) developing a novel clustering technique to identify multi-scale clustering structures in Planar Filtered Networks (PFNs). We applied MEGENA to a series of simulated data and the geneexpression data in breast carcinoma and lung adenocarcinoma from The Cancer Genome Atlas (TCGA). MEGENA showed improved performance over well-established clustering methods and co-expression network construction approaches. MEGENA revealed not only meaningful multi-scale organizations of co-expressedgene clusters but also novel targets in breast carcinoma and lung adenocarcinoma.

The merging of molecular biology and nuclear medicine is developed into molecular nuclear medicine. Positron emission tomography (PET) of geneexpression in molecular nuclear medicine has become an attractive area. Positron emission tomography imaging geneexpression includes the antisense PET imaging and the reporter gene PET imaging. It is likely that the antisense PET imaging will lag behind the reporter gene PET imaging because of the numerous issues that have not yet to be resolved with this approach. The reporter gene PET imaging has wide application into animal experimental research and human applications of this approach will likely be reported soon

Full Text Available Abstract Background Large-scale quantitative analysis of transcriptional co-expression has been used to dissect regulatory networks and to predict the functions of new genes discovered by genome sequencing in model organisms such as yeast. Although the idea that tissue-specific expression is indicative of gene function in mammals is widely accepted, it has not been objectively tested nor compared with the related but distinct strategy of correlating gene co-expression as a means to predict gene function. Results We generated microarray expression data for nearly 40,000 known and predicted mRNAs in 55 mouse tissues, using custom-built oligonucleotide arrays. We show that quantitative transcriptional co-expression is a powerful predictor of gene function. Hundreds of functional categories, as defined by Gene Ontology 'Biological Processes', are associated with characteristic expression patterns across all tissues, including categories that bear no overt relationship to the tissue of origin. In contrast, simple tissue-specific restriction of expression is a poor predictor of which genes are in which functional categories. As an example, the highly conserved mouse gene PWP1 is widely expressed across different tissues but is co-expressed with many RNA-processing genes; we show that the uncharacterized yeast homolog of PWP1 is required for rRNA biogenesis. Conclusions We conclude that 'functional genomics' strategies based on quantitative transcriptional co-expression will be as fruitful in mammals as they have been in simpler organisms, and that transcriptional control of mammalian physiology is more modular than is generally appreciated. Our data and analyses provide a public resource for mammalian functional genomics.

The gonadal soma-derived factor (GSDF) belongs to the transforming growth factor-β superfamily and is conserved in teleostean fish species. Gsdf is specifically expressed in the gonads, and geneexpression is restricted to the granulosa and Sertoli cells in trout and medaka. The gsdf geneexpression is correlated to early testis differentiation in medaka and was shown to stimulate primordial germ cell and spermatogonia proliferation in trout. In the present study, we show that the gsdf gene localizes to a syntenic chromosomal fragment conserved among vertebrates although no gsdf-related gene is detected on the corresponding genomic region in tetrapods. We demonstrate using quantitative RT-PCR that most of the genes localized in the synteny are specifically expressed in medaka gonads. Gsdf is the only gene of the synteny with a much higher expression in the testis compared to the ovary. In contrast, geneexpression pattern analysis of the gsdf surrounding genes (nup54, aff1, klhl8, sdad1, and ptpn13) indicates that these genes are preferentially expressed in the female gonads. The tissue distribution of these genes is highly similar in medaka and zebrafish, two teleostean species that have diverged more than 110 million years ago. The cellular localization of these genes was determined in medaka gonads using the whole-mount in situ hybridization technique. We confirm that gsdf geneexpression is restricted to Sertoli and granulosa cells in contact with the premeiotic and meiotic cells. The nup54 gene is expressed in spermatocytes and previtellogenic oocytes. Transcripts corresponding to the ovary-specific genes (aff1, klhl8, and sdad1) are detected only in previtellogenic oocytes. No expression was detected in the gonocytes in 10 dpf embryos. In conclusion, we show that the gsdf gene localizes to a syntenic chromosomal fragment harboring evolutionary conserved genes in vertebrates. These genes are preferentially expressed in previtelloogenic oocytes, and thus, they

Full Text Available Abstract Background As whole genome and transcriptome sequencing gets cheaper and faster, a great number of 'exotic' animal models are emerging, rapidly adding valuable data to the ever-expanding Evo-Devo field. All these new organisms serve as a fantastic resource for the research community, but the sheer amount of data, some published, some not, makes detailed comparison of geneexpression patterns very difficult to summarize - a problem sometimes even noticeable within a single lab. The need to merge existing data with new information in an organized manner that is publicly available to the research community is now more necessary than ever. Description In order to offer a homogenous way of storing and handling geneexpression patterns from a variety of organisms, we have developed the first web-based comparative geneexpression database for invertebrates that allows species-specific as well as cross-species geneexpression comparisons. The database can be queried by gene name, developmental stage and/or expression domains. Conclusions This database provides a unique tool for the Evo-Devo research community that allows the retrieval, analysis and comparison of geneexpression patterns within or among species. In addition, this database enables a quick identification of putative syn-expression groups that can be used to initiate, among other things, gene regulatory network (GRN projects.

Full Text Available The transformation of epimastigotes into metacyclic trypomastigotes involves changes in the pattern of expressedgenes, resulting in important morphological and functional differences between these developmental forms of Trypanosoma cruzi. In order to identify and characterize genes involved in triggering the metacyclogenesis process and in conferring to metacyclic trypomastigotes their stage specific biological properties, we have developed a method allowing the isolation of genes specifically expressed when comparing two close related cell populations (representation of differential expression or RDE. The method is based on the PCR amplification of gene sequences selected by hybridizing and subtracting the populations in such a way that after some cycles of hybridization-amplification genes specific to a given population are highly enriched. The use of this method in the analysis of differential geneexpression during T. cruzi metacyclogenesis (6 hr and 24 hr of differentiation and metacyclic trypomastigotes resulted in the isolation of several clones from each time point. Northern blot analysis showed that some genes are transiently expressed (6 hr and 24 hr differentiating cells, while others are present in differentiating cells and in metacyclic trypomastigotes. Nucleotide sequencing of six clones characterized so far showed that they do not display any homology to gene sequences available in the GeneBank.

DAR algorithm not only was able to identify a set of differentially expressedgenes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to geneexpression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

Although plant development is highly reproducible, some stochasticity exists. This developmental stochasticity may be caused by noisy geneexpression. Here we analyze the fluctuation of protein expression in Arabidopsis thaliana. Using the photoconvertible KikGR marker, we show that the protein expressions of individual cells fluctuate over time. A dual reporter system was used to study extrinsic and intrinsic noise of marker geneexpression. We report that extrinsic noise is higher than intrinsic noise and that extrinsic noise in stomata is clearly lower in comparison to several other tissues/cell types. Finally, we show that cells are coupled with respect to stochastic protein expression in young leaves, hypocotyls and roots but not in mature leaves. Our data indicate that stochasticity of geneexpression can vary between tissues/cell types and that it can be coupled in a non-cell-autonomous manner.

Full Text Available Geneexpression analysis in watermelon (Citrullus lanatus fruit has drawn considerable attention with the availability of genome sequences to understand the regulatory mechanism of fruit development and to improve its quality. Real-time quantitative reverse-transcription PCR (qRT-PCR is a routine technique for geneexpression analysis. However, appropriate reference genes for transcript normalization in watermelon fruits have not been well characterized. The aim of this study was to evaluate the appropriateness of 12 genes for their potential use as reference genes in watermelon fruits. Expression variations of these genes were measured in 48 samples obtained from 12 successive developmental stages of parthenocarpic and fertilized fruits of two watermelon genotypes by using qRT-PCR analysis. Considering the effects of genotype, fruit setting method, and developmental stage, geNorm determined clathrin adaptor complex subunit (ClCAC, β-actin (ClACT, and alpha tubulin 5 (ClTUA5 as the multiple reference genes in watermelon fruit. Furthermore, ClCAC alone or together with SAND family protein (ClSAND was ranked as the single or two best reference genes by NormFinder. By using the top-ranked reference genes to normalize the transcript abundance of phytoene synthase (ClPSY1, a good correlation between lycopene accumulation and ClPSY1 expression pattern was observed in ripening watermelon fruit. These validated reference genes will facilitate the accurate measurement of geneexpression in the studies on watermelon fruit biology.

Geneexpression analysis in watermelon (Citrullus lanatus) fruit has drawn considerable attention with the availability of genome sequences to understand the regulatory mechanism of fruit development and to improve its quality. Real-time quantitative reverse-transcription PCR (qRT-PCR) is a routine technique for geneexpression analysis. However, appropriate reference genes for transcript normalization in watermelon fruits have not been well characterized. The aim of this study was to evaluate the appropriateness of 12 genes for their potential use as reference genes in watermelon fruits. Expression variations of these genes were measured in 48 samples obtained from 12 successive developmental stages of parthenocarpic and fertilized fruits of two watermelon genotypes by using qRT-PCR analysis. Considering the effects of genotype, fruit setting method, and developmental stage, geNorm determined clathrin adaptor complex subunit (ClCAC), β-actin (ClACT), and alpha tubulin 5 (ClTUA5) as the multiple reference genes in watermelon fruit. Furthermore, ClCAC alone or together with SAND family protein (ClSAND) was ranked as the single or two best reference genes by NormFinder. By using the top-ranked reference genes to normalize the transcript abundance of phytoene synthase (ClPSY1), a good correlation between lycopene accumulation and ClPSY1 expression pattern was observed in ripening watermelon fruit. These validated reference genes will facilitate the accurate measurement of geneexpression in the studies on watermelon fruit biology.

Full Text Available Abstract Background In periodontitis, treatment aimed at controlling the periodontal biofilm infection results in a resolution of the clinical and histological signs of inflammation. Although the cell types found in periodontal tissues following treatment have been well described, information on geneexpression is limited to few candidate genes. Therefore, the aim of the study was to determine the expression profiles of immune and inflammatory genes in periodontal tissues from sites with severe chronic periodontitis following periodontal therapy in order to identify genes involved in tissue homeostasis. Gingival biopsies from 12 patients with severe chronic periodontitis were taken six to eight weeks following non-surgical periodontal therapy, and from 11 healthy controls. As internal standard, RNA of an immortalized human keratinocyte line (HaCaT was used. Total RNA was subjected to geneexpression profiling using a commercially available microarray system focusing on inflammation-related genes. Post-hoc confirmation of selected genes was done by Realtime-PCR. Results Out of the 136 genes analyzed, the 5% most strongly expressedgenes compared to healthy controls were Interleukin-12A (IL-12A, Versican (CSPG-2, Matrixmetalloproteinase-1 (MMP-1, Down syndrome critical region protein-1 (DSCR-1, Macrophage inflammatory protein-2β (Cxcl-3, Inhibitor of apoptosis protein-1 (BIRC-1, Cluster of differentiation antigen 38 (CD38, Regulator of G-protein signalling-1 (RGS-1, and Finkel-Biskis-Jinkins murine osteosarcoma virus oncogene (C-FOS; the 5% least strongly expressedgenes were Receptor-interacting Serine/Threonine Kinase-2 (RIP-2, Complement component 3 (C3, Prostaglandin-endoperoxide synthase-2 (COX-2, Interleukin-8 (IL-8, Endothelin-1 (EDN-1, Plasminogen activator inhibitor type-2 (PAI-2, Matrix-metalloproteinase-14 (MMP-14, and Interferon regulating factor-7 (IRF-7. Conclusion Geneexpression profiles found in periodontal tissues following

Full Text Available Abstract Background Olfactory receptors (ORs are the largest gene family in the human genome. Although they are expected to be expressed specifically in olfactory tissues, some ectopic expression has been reported, with special emphasis on sperm and testis. The present study systematically explores the expression patterns of OR genes in a large number of tissues and assesses the potential functional implication of such ectopic expression. Results We analyzed the expression of hundreds of human and mouse OR transcripts, via EST and microarray data, in several dozens of human and mouse tissues. Different tissues had specific, relatively small OR gene subsets which had particularly high expression levels. In testis, average expression was not particularly high, and very few highly expressedgenes were found, none corresponding to ORs previously implicated in sperm chemotaxis. Higher expression levels were more common for genes with a non-OR genomic neighbor. Importantly, no correlation in expression levels was detected for human-mouse orthologous pairs. Also, no significant difference in expression levels was seen between intact and pseudogenized ORs, except for the pseudogenes of subfamily 7E which has undergone a human-specific expansion. Conclusion The OR superfamily as a whole, show widespread, locus-dependent and heterogeneous expression, in agreement with a neutral or near neutral evolutionary model for transcription control. These results cannot reject the possibility that small OR subsets might play functional roles in different tissues, however considerable care should be exerted when offering a functional interpretation for ectopic OR expression based only on transcription information.

Full Text Available Abstract Background Real-time reverse transcriptase quantitative polymerase chain reaction (real-time RTqPCR is a technique used to measure mRNA species copy number as a way to determine key genes involved in different biological processes. However, the expression level of these key genes may vary among tissues or cells not only as a consequence of differential expression but also due to different factors, including choice of reference genes to normalize the expression levels of the target genes; thus the selection of reference genes is critical for expression studies. For this purpose, ten candidate reference genes were investigated in bovine muscular tissue. Results The value of stability of ten candidate reference genes included in three groups was estimated: the so called 'classical housekeeping' genes (18S, GAPDH and ACTB, a second set of genes used in expression studies conducted on other tissues (B2M, RPII, UBC and HMBS and a third set of novel genes (SF3A1, EEF1A2 and CASC3. Three different statistical algorithms were used to rank the genes by their stability measures as produced by geNorm, NormFinder and Bestkeeper. The three methods tend to agree on the most stably expressedgenes and the least in muscular tissue. EEF1A2 and HMBS followed by SF3A1, ACTB, and CASC3 can be considered as stable reference genes, and B2M, RPII, UBC and GAPDH would not be appropriate. Although the rRNA-18S stability measure seems to be within the range of acceptance, its use is not recommended because its synthesis regulation is not representative of mRNA levels. Conclusion Based on geNorm algorithm, we propose the use of three genes SF3A1, EEF1A2 and HMBS as references for normalization of real-time RTqPCR in muscle expression studies.

Full Text Available Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into geneexpression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of geneexpression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of geneexpression in Plasmodium sp., Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.

Infections with protozoa parasites are associated with high burdens of morbidity and mortality across the developing world. Despite extensive efforts to control the transmission of these parasites, the spread of populations resistant to drugs and the lack of effective vaccines against them contribute to their persistence as major public health problems. Parasites should perform a strict control on the expression of genes involved in their pathogenicity, differentiation, immune evasion, or drug resistance, and the comprehension of the mechanisms implicated in that control could help to develop novel therapeutic strategies. However, until now these mechanisms are poorly understood in protozoa. Recent investigations into geneexpression in protozoa parasites suggest that they possess many of the canonical machineries employed by higher eukaryotes for the control of geneexpression at transcriptional, posttranscriptional, and epigenetic levels, but they also contain exclusive mechanisms. Here, we review the current understanding about the regulation of geneexpression in Plasmodium sp., Trypanosomatids, Entamoeba histolytica and Trichomonas vaginalis.

graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of geneexpression, and RNA-sequencing experiments, both of which

National Aeronautics and Space Administration — Geneexpression levels were determined in 3rd instar and adult Drosophila melanogaster reared during spaceflight to elucidate the genetic and molecular mechanisms...

Microarray analysis of geneexpression at the level of RNA has generated new insights into the relationship between cellular responses to acute heat shock in vitro, exercise, and exertional heat illness...

Full Text Available With the recent advances in genomics and sequencing technologies, databases of transcriptomes representing many cellular processes have been built. Meiotic transcriptomes in plants have been studied in Arabidopsis thaliana, rice (Oryza sativa, wheat (Triticum aestivum, petunia (Petunia hybrida, sunflower (Helianthus annuus, and maize (Zea mays. Studies in all organisms, but particularly in plants, indicate that a very large number of genes are expressed during meiosis, though relatively few of them seem to be required for the completion of meiosis. In this review, we focus on geneexpression at the RNA level and analyze the meiotic transcriptome datasets and explore expression patterns of known meiotic genes to elucidate how geneexpression could be regulated during meiosis. We also discuss mechanisms, such as chromatin organization and non-coding RNAs, that might be involved in the regulation of meiotic transcription patterns.

Full Text Available Microarray produces a large amount of geneexpression data, containing various biological implications. The challenge is to detect a panel of discriminative genes associated with disease. This study proposed a robust classification model for gene selection using geneexpression data, and performed an analysis to identify disease-related genes using multiple sclerosis as an example.Geneexpression profiles based on the transcriptome of peripheral blood mononuclear cells from a total of 44 samples from 26 multiple sclerosis patients and 18 individuals with other neurological diseases (control were analyzed. Feature selection algorithms including Support Vector Machine based on Recursive Feature Elimination, Receiver Operating Characteristic Curve, and Boruta algorithms were jointly performed to select candidate genes associating with multiple sclerosis. Multiple classification models categorized samples into two different groups based on the identified genes. Models' performance was evaluated using cross-validation methods, and an optimal classifier for gene selection was determined.An overlapping feature set was identified consisting of 8 genes that were differentially expressed between the two phenotype groups. The genes were significantly associated with the pathways of apoptosis and cytokine-cytokine receptor interaction. TNFSF10 was significantly associated with multiple sclerosis. A Support Vector Machine model was established based on the featured genes and gave a practical accuracy of ∼86%. This binary classification model also outperformed the other models in terms of Sensitivity, Specificity and F1 score.The combined analytical framework integrating feature ranking algorithms and Support Vector Machine model could be used for selecting genes for other diseases.

Trichomonas vaginalis is the etiologic agent of trichomonosis, the most common non-viral sexually transmitted disease worldwide. This infection is associated with several health consequences, including cervical and prostate cancers and HIV acquisition. Geneexpression analysis has been facilitated because of available genome sequences and large-scale transcriptomes in T. vaginalis, particularly using quantitative real-time polymerase chain reaction (qRT-PCR), one of the most used methods for molecular studies. Reference genes for normalization are crucial to ensure the accuracy of this method. However, to the best of our knowledge, a systematic validation of reference genes has not been performed for T. vaginalis. In this study, the transcripts of nine candidate reference genes were quantified using qRT-PCR under different cultivation conditions, and the stability of these genes was compared using the geNorm and NormFinder algorithms. The most stable reference genes were α-tubulin, actin and DNATopII, and, conversely, the widely used T. vaginalis reference genes GAPDH and β-tubulin were less stable. The PFOR gene was used to validate the reliability of the use of these candidate reference genes. As expected, the PFOR gene was upregulated when the trophozoites were cultivated with ferrous ammonium sulfate when the DNATopII, α-tubulin and actin genes were used as normalizing gene. By contrast, the PFOR gene was downregulated when the GAPDH gene was used as an internal control, leading to misinterpretation of the data. These results provide an important starting point for reference gene selection and geneexpression analysis with qRT-PCR studies of T. vaginalis. PMID:26393928

Dec 14, 2011 ... MADS family of TFs control floral organ identity within each whorl of the flower by activating downstream genes. Measuring geneexpression in different tissue types and developmental stages is of fundamental importance in TFs functional research. In last few years, quantitative real-time. PCR (qRT-PCR) ...

Full Text Available Medulloblastoma is the most common malignant tumors of central nervous system in the childhood. The treatment is severe, harmful and, thus, has a dismal prognosis. As PRAME is present in various cancers, including meduloblastoma, and has limited expression in normal tissues, this antigen can be an ideal vaccine target for tumor immunotherapy. In order to find a potential molecular target, we investigated PRAME expression in medulloblastoma fragments and we compare the results with the clinical features of each patient. Analysis of geneexpression was performed by real-time quantitative PCR from 37 tumor samples. The Mann-Whitney test was used to analysis the relationship between geneexpression and clinical characteristics. Kaplan-Meier curves were used to evaluate survival. PRAME was overexpressed in 84% samples. But no statistical association was found between clinical features and PRAME overexpression. Despite that PRAME gene could be a strong candidate for immunotherapy since it is highly expressed in medulloblastomas.

Full Text Available Abstract Background Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository. Results In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species geneexpression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences. Conclusions Taken together, these analyses provide a global view of geneexpression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

A central issue in autoimmune disease is whether the underlying inflammation is a repeated stereotypical process or whether disease specific geneexpression is involved. To shed light on this, we analysed whether genes previously found to be differentially regulated in rheumatoid arthritis (RA...

Geneexpression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Source code under GPL license is available from the author. peter.sykacek@boku.ac.at.

Motivation: Geneexpression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment. Results: This article proposes a probabilistic model for GO term inference. Modelling assumes that gene annotations to GO terms are available and gene involvement in an experiment is represented by a posterior probabilities over gene-specific indicator variables. Such probability measures result from many Bayesian approaches for expression data analysis. The proposed model combines these indicator probabilities in a probabilistic fashion and provides a probabilistic GO term assignment as a result. Experiments on synthetic and microarray data suggest that advantages of the proposed probabilistic GO term inference over statistical test-based approaches are in particular evident for sparsely annotated GO terms and in situations of large uncertainty about gene activity. Provided that appropriate annotations exist, the proposed approach is easily applied to inferring other high level assignments like pathways. Availability: Source code under GPL license is available from the author. Contact: peter.sykacek@boku.ac.at PMID:22962488

Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcrip...

Full Text Available Real-time quantitative PCR (qRT-PCR is one of the important methods for investigating the changes in mRNA expression levels in cells and tissues. Selection of the proper reference genes is very important when calibrating the results of real-time quantitative PCR. Studies on the selection of reference genes in goat tissues are limited, despite the economic importance of their meat and dairy products. We used real-time quantitative PCR to detect the expression levels of eight reference gene candidates (18S, TBP, HMBS, YWHAZ, ACTB, HPRT1, GAPDH and EEF1A2 in ten tissues types sourced from Boer goats. The optimal reference gene combination was selected according to the results determined by geNorm, NormFinder and Bestkeeper software packages. The analyses showed that tissue is an important variability factor in genesexpression stability. When all tissues were considered, 18S, TBP and HMBS is the optimal reference combination for calibrating quantitative PCR analysis of geneexpression from goat tissues. Dividing data set by tissues, ACTB was the most stable in stomach, small intestine and ovary, 18S in heart and spleen, HMBS in uterus and lung, TBP in liver, HPRT1 in kidney and GAPDH in muscle. Overall, this study provided valuable information about the goat reference genes that can be used in order to perform a proper normalisation when relative quantification by qRT-PCR studies is undertaken.

Full Text Available Abstract Background Insertional mutagenesis techniques with transposable elements have been popular among geneticists studying model organisms from E. coli to Drosophila and, more recently, the mouse. One such element is the Sleeping Beauty (SB transposon that has been shown in several studies to be an effective insertional mutagen in the mouse germline. SB transposon vector studies have employed different functional elements and reporter molecules to disrupt and report the expression of endogenous mouse genes. We sought to generate a transposon system that would be capable of reporting the expression pattern of a mouse gene while allowing for conditional expression of a gene of interest in a tissue- or temporal-specific pattern. Results Here we report the systematic development and testing of a transposon-based gene-trap system incorporating the doxycycline-repressible Tet-Off (tTA system that is capable of activating the expression of genes under control of a Tet response element (TRE promoter. We demonstrate that the gene trap system is fully functional in vitro by introducing the "gene-trap tTA" vector into human cells by transposition and identifying clones that activate expression of a TRE-luciferase transgene in a doxycycline-dependent manner. In transgenic mice, we mobilize gene-trap tTA vectors, discover parameters that can affect germline mobilization rates, and identify candidate gene insertions to demonstrate the in vivo functionality of the vector system. We further demonstrate that the gene-trap can act as a reporter of endogenous geneexpression and it can be coupled with bioluminescent imaging to identify genes with tissue-specific expression patterns. Conclusion Akin to the GAL4/UAS system used in the fly, we have made progress developing a tool for mutating and revealing the expression of mouse genes by generating the tTA transactivator in the presence of a secondary TRE-regulated reporter molecule. A vector like the gene

Full Text Available All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or "noise." Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic geneexpression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in geneexpression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic geneexpression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in geneexpression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic geneexpression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in geneexpression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection

Full Text Available Banana is one of the world's most important trade commodities. However, infection of banana pathogenic fungi (Fusarium oxysporum race 4 is one of the major causes of decreasing production in Indonesia. Genetic engineering has become an alternative way to control this problem by isolating genes that involved in plant defense mechanism against pathogens. Two of the important genes are API5 and ChiI1, each gene encodes apoptosis inhibitory protein and chitinase enzymes. The purpose of this study was to study the expression of API5 and ChiI1 genes as candidate pathogenic resistance genes. The amplified fragments were then cloned, sequenced, and confirmed with in silico studies. Based on sequence analysis, it is showed that partial API5 gene has putative transactivation domain and ChiI1 has 9 chitinase family GH19 protein motifs. Data obtained from this study will contribute in banana genetic improvement.

Skeletal growth and homeostasis require the finely orchestrated secretion of mineralized tissue matrices by highly specialized cells, balanced with their degradation by osteoclasts. Time- and site-specific expression of Dlx and Msx homeobox genes in the cells secreting these matrices have been identified as important elements in the regulation of skeletal morphology. Such specific expression patterns have also been reported in osteoclasts for Msx genes. The aim of the present study was to establish the expression patterns of Dlx genes in osteoclasts and identify their function in regulating skeletal morphology. The expression patterns of all Dlx genes were examined during the whole osteoclastogenesis using different in vitro models. The results revealed that Dlx1 and Dlx2 are the only Dlx family members with a possible function in osteoclastogenesis as well as in mature osteoclasts. Dlx5 and Dlx6 were detected in the cultures but appear to be markers of monocytes and their derivatives. In vivo, Dlx2 expression in osteoclasts was examined using a Dlx2/LacZ transgenic mouse. Dlx2 is expressed in a subpopulation of osteoclasts in association with tooth, brain, nerve, and bone marrow volumetric growths. Altogether the present data suggest a role for Dlx2 in regulation of skeletal morphogenesis via functions within osteoclasts. (c) 2010 Wiley-Liss, Inc.

Full Text Available Abstract Background One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between geneexpression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between geneexpression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. Results We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both geneexpression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I, decreased (D, or not changed (N. As a result, the original series of n geneexpression level measures assigned to each gene is replaced by an ordered string of n(n-1/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their

The native nature of high dimension low sample size of geneexpression data make the classification task more challenging. Therefore, feature (gene) selection become an apparent need. Selecting a meaningful and relevant genes for classifier not only decrease the computational time and cost, but also improve the classification performance. Among different approaches of feature selection methods, however most of them suffer from several problems such as lack of robustness, validation issues etc. Here, we present a new feature selection technique that takes advantage of clustering both samples and genes. Materials and methods We used leukemia geneexpression dataset [1]. The effectiveness of the selected features were evaluated by four different classification methods; support vector machines, k-nearest neighbor, random forest, and linear discriminate analysis. The method evaluate the importance and relevance of each gene cluster by summing the expression level for each gene belongs to this cluster. The gene cluster consider important, if it satisfies conditions depend on thresholds and percentage otherwise eliminated. Results Initial analysis identified 7120 differentially expressedgenes of leukemia (Fig. 15a), after applying our feature selection methodology we end up with specific 1117 genes discriminating two classes of leukemia (Fig. 15b). Further applying the same method with more stringent higher positive and lower negative threshold condition, number reduced to 58 genes have be tested to evaluate the effectiveness of the method (Fig. 15c). The results of the four classification methods are summarized in Table 11. Conclusions The feature selection method gave good results with minimum classification error. Our heat-map result shows distinct pattern of refines genes discriminating between two classes of leukemia.

Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages) seed coats (globular and torpedo stages) and endosperm (pooled globular to torpedo stages) and genesexpressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST) (GenBank accessions LIBEST_026995 to LIBEST_027011) were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152) had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed geneexpression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid clones that comprise

Full Text Available Abstract Background Flax, Linum usitatissimum L., is an important crop whose seed oil and stem fiber have multiple industrial applications. Flax seeds are also well-known for their nutritional attributes, viz., omega-3 fatty acids in the oil and lignans and mucilage from the seed coat. In spite of the importance of this crop, there are few molecular resources that can be utilized toward improving seed traits. Here, we describe flax embryo and seed development and generation of comprehensive genomic resources for the flax seed. Results We describe a large-scale generation and analysis of expressed sequences in various tissues. Collectively, the 13 libraries we have used provide a broad representation of genes active in developing embryos (globular, heart, torpedo, cotyledon and mature stages seed coats (globular and torpedo stages and endosperm (pooled globular to torpedo stages and genesexpressed in flowers, etiolated seedlings, leaves, and stem tissue. A total of 261,272 expressed sequence tags (EST (GenBank accessions LIBEST_026995 to LIBEST_027011 were generated. These EST libraries included transcription factor genes that are typically expressed at low levels, indicating that the depth is adequate for in silico expression analysis. Assembly of the ESTs resulted in 30,640 unigenes and 82% of these could be identified on the basis of homology to known and hypothetical genes from other plants. When compared with fully sequenced plant genomes, the flax unigenes resembled poplar and castor bean more than grape, sorghum, rice or Arabidopsis. Nearly one-fifth of these (5,152 had no homologs in sequences reported for any organism, suggesting that this category represents genes that are likely unique to flax. Digital analyses revealed geneexpression dynamics for the biosynthesis of a number of important seed constituents during seed development. Conclusions We have developed a foundational database of expressed sequences and collection of plasmid

Serial analysis of geneexpression (SAGE) and microarrays have found a widespread application, but much ambiguity exists regarding the amalgamation of the data resulting from these technologies. Cross-platform utilization of geneexpression data from the SAGE and microarray technology could reduce

We present a bioinformatics database named Renal GeneExpression Database (RGED), which contains comprehensive geneexpression data sets from renal disease research. The web-based interface of RGED allows users to query the geneexpression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

Full text: We use the nematode C. elegans to characterize the genotoxic and cytotoxic effects of ionizing radiation with emphasis effects of charged particle radiation and have described the fluence vs. response relationships for mutation, chromosome aberration and certain developmental errors. These endpoints quantify the biological after repair and compensation pathways have completed their work. In order to address the control of these reactions we have turned to geneexpression profiling to identify genes that uniquely respond to high LET species or respond differentially as a function of radiation properties. We have employed whole genome microarray methods to map geneexpression following exposure to gamma rays, protons and accelerated iron ions. We found that 599 of 17871 genes analyzed showed differential expression 3 hrs after exposure to 3 Gy of at least one radiation types. 193 were up-regulated, 406 were down-regulated, and 90% were affected by only one species of radiation. Genes whose transcription levels responded significantly mapped to definite statistical clusters that were unique for each radiation type. We are now trying to establish the functional relationships of the genes their relevance to mitigation of radiation-induced damage. Three approaches are being used. First, bioinformatics tools are being used to determine the roles of genes in co-regulated gene sets. Second, we are applying the technique of RNA interference to determine whether our radiation-induced genes affect cell survival (measured in terms of embryo survival) and chromosome aberration (intestinal anaphase bridges). Finally we are focussing on the response of the most strongly-regulated gene in our data set. This is the autosomal gene, F36D3.9, whose predicted structure is that of a cysteine protease resembling cathepsin B. An enzymological approach is being used to characterize this gene at the protein level. This work was supported by NASA Cooperative Agreement NCC9-149

Recent findings indicate an important role for RNA-mediated geneexpression in motor neuron diseases, including ALS (amyotrophic lateral sclerosis) and SMA (spinal muscular atrophy). ALS, also known as Lou Gehrig's disease, is an adult-onset progressive neurodegenerative disorder, whereby SMA or "children's Lou Gehrig's disease" is considered a pediatric neurodevelopmental disorder. Despite the difference in genetic causes, both ALS and SMA share common phenotypes; dysfunction/loss of motor neurons that eventually leads to muscle weakness and atrophy. With advanced techniques in molecular genetics and cell biology, current data suggest that these two distinct motor neuron diseases share more than phenotypes; ALS and SMA have similar cellular pathological mechanisms including mitochondrial dysfunction, oxidative stress and dysregulation in RNA-mediated geneexpression. Here, we will discuss the current findings on these two diseases with specific focus on RNA-mediated gene regulation including miRNA expression, pre-mRNA processing and RNA binding proteins.

Background Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of geneexpression. A novel computational approach to the study of gene regulation circuits is presented here. Methodology Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM) is developed to decipher control mechanisms of dynamic transcriptional regulation of geneexpressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. Principal Findings SLM is verified by a set of well studied expression data on endo16 of Strongylocentrotus purpuratus (sea urchin) during the embryonic midgut development. A dynamic regulatory mechanism for endo16 expression controlled by three binding sites, UI, R and Otx is identified and demonstrated to be consistent with experimental findings. Furthermore, we show that during transition from specification to differentiation in wild type endo16 expression profile, SLM reveals three binary activities are not sufficient to explain the transcriptional regulation of endo16 expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. Conclusions/Significance The sequential logic formalism allows for a simplification of regulation network dynamics going from a continuous to a discrete representation of gene activation in time. In effect our SLM is non-parametric and model-independent, yet providing rich biological

Full Text Available BACKGROUND: Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of geneexpression. A novel computational approach to the study of gene regulation circuits is presented here. METHODOLOGY: Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM is developed to decipher control mechanisms of dynamic transcriptional regulation of geneexpressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. PRINCIPAL FINDINGS: SLM is verified by a set of well studied expression data on endo16 of Strongylocentrotus purpuratus (sea urchin during the embryonic midgut development. A dynamic regulatory mechanism for endo16 expression controlled by three binding sites, UI, R and Otx is identified and demonstrated to be consistent with experimental findings. Furthermore, we show that during transition from specification to differentiation in wild type endo16 expression profile, SLM reveals three binary activities are not sufficient to explain the transcriptional regulation of endo16 expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. CONCLUSIONS/SIGNIFICANCE: The sequential logic formalism allows for a simplification of regulation network dynamics going from a continuous to a discrete representation of gene activation in time. In effect our SLM is non-parametric and model-independent, yet

Full Text Available Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE. All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others. The understanding of expressedgenes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

Sleep is governed by homeostasis and the circadian clock. Clock genes play an important role in the generation and maintenance of circadian rhythms but are also involved in regulating sleep homeostasis. The lateral habenular nucleus (LHb) has been implicated in sleep-wake regulation, since LHb geneexpression demonstrates circadian oscillation characteristics. This study focuses on the participation of LHb clock genes in regulating sleep homeostasis, as the nature of their involvement is unclear. In this study, we observed changes in sleep pattern following sleep deprivation in LHb-lesioned rats using EEG recording techniques. And then the changes of clock geneexpression (Per1, Per2, and Bmal1) in the LHb after 6 hours of sleep deprivation were detected by using real-time quantitative PCR (qPCR). We found that sleep deprivation increased the length of Non-Rapid Eye Movement Sleep (NREMS) and decreased wakefulness. LHb-lesioning decreased the amplitude of reduced wake time and increased NREMS following sleep deprivation in rats. qPCR results demonstrated that Per2 expression was elevated after sleep deprivation, while the other two genes were unaffected. Following sleep recovery, Per2 expression was comparable to the control group. This study provides the basis for further research on the role of LHb Per2 gene in the regulation of sleep homeostasis.

Since the second half of the 1990s, a large number of genome-wide analyses have been described that study geneexpression at the transcript level. To this end, two major strategies have been adopted, a first one relying on hybridization techniques such as microarrays, and a second one based on sequencing techniques such as serial analysis of geneexpression (SAGE), cDNA-AFLP, and analysis based on expressed sequence tags (ESTs). Despite both types of profiling experiments becoming routine techniques in many research groups, their application remains costly and laborious. As a result, the number of conditions profiled in individual studies is still relatively small and usually varies from only two to few hundreds of samples for the largest experiments. More and more, scientific journals require the deposit of these high throughput experiments in public databases upon publication. Mining the information present in these databases offers molecular biologists the possibility to view their own small-scale analysis in the light of what is already available. However, so far, the richness of the public information remains largely unexploited. Several obstacles such as the correct association between ESTs and microarray probes with the corresponding gene transcript, the incompleteness and inconsistency in the annotation of experimental conditions, and the lack of standardized experimental protocols to generate geneexpression data, all impede the successful mining of these data. Here, we review the potential and difficulties of combining publicly available expression data from respectively EST analyses and microarray experiments. With examples from literature, we show how meta-analysis of expression profiling experiments can be used to study expression behavior in a single organism or between organisms, across a wide range of experimental conditions. We also provide an overview of the methods and tools that can aid molecular biologists in exploiting these public data.

Moringa oleifera is a promising plant species for oil and forage, but its genetic improvement is limited. Our current breeding program in this species focuses on exploiting the functional genes associated with important agronomical traits. Here, we screened reliable reference genes for accurately quantifying the expression of target genes using the technique of real-time quantitative polymerase chain reaction (RT-qPCR) in M. oleifera. Eighteen candidate reference genes were selected from a transcriptome database, and their expression stabilities were examined in 90 samples collected from the pods in different developmental stages, various tissues, and the roots and leaves under different conditions (low or high temperature, sodium chloride (NaCl)- or polyethyleneglycol (PEG)- simulated water stress). Analyses with geNorm, NormFinder and BestKeeper algorithms revealed that the reliable reference genes differed across sample designs and that ribosomal protein L1 (RPL1) and acyl carrier protein 2 (ACP2) were the most suitable reference genes in all tested samples. The experiment results demonstrated the significance of using the properly validated reference genes and suggested the use of more than one reference gene to achieve reliable expression profiles. In addition, we applied three isotypes of the superoxide dismutase (SOD) gene that are associated with plant adaptation to abiotic stress to confirm the efficacy of the validated reference genes under NaCl and PEG water stresses. Our results provide a valuable reference for future studies on identifying important functional genes from their transcriptional expressions via RT-qPCR technique in M. oleifera.

Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change geneexpression levels, it is not clear whether each individual SCNA affects gen...

Full Text Available Introduction: Metallothioneins (MTs are a group of low-molecular weight, cysteine-rich proteins. In general, MT is known to modulate three fundamental processes: (1 the release of gaseous mediators such as hydroxyl radical or nitric oxide, (2 apoptosis and (3 the binding and exchange of heavy metals such as zinc, cadmium or copper. Previous studies have shown a positive correlation between the expression of MT with invasion, metastasis and poor prognosis in various cancers. Most of the previous studies primarily used immunohistochemistry to analyze localization of MT in renal cell carcinoma (RCC. No information is available on the geneexpression of MT2A isoform in different types and grades of RCC. Materials and Methods: In the present study, total RNA was isolated from 38 histopathologically confirmed cases of RCC of different types and grades. Corresponding adjacent normal renal parenchyma was taken as control. Real-time polymerase chain reaction (RT PCR analysis was done for the MT2A geneexpression using b-actin as an internal control. All statistical calculations were performed using SPSS software. Results: The MT2A geneexpression was found to be significantly increased (P < 0.01 in clear cell RCC in comparison with the adjacent normal renal parenchyma. The expression of MT2A was two to three-fold higher in sarcomatoid RCC, whereas there was no change in papillary and collecting duct RCC. MT2A geneexpression was significantly higher in lower grade (grades I and II, P < 0.05, while no change was observed in high-grade tumor (grade III and IV in comparison to adjacent normal renal tissue. Conclusion: The first report of the expression of MT2A in different types and grades of RCC and also these data further support the role of MT2A in tumorigenesis.

that the endolymphatic sac has multiple and diverse functions in the inner ear. Objectives:The objective of this study was to provide a comprehensive review of the genesexpressed in the endolymphatic sac in the rat and perform a functional characterization based on measured mRNA abundance. Methods:Microarray technology...

Objective. Pelvic lymph node metastases are the main prognostic factor for survival in early stage cervical cancer, yet accurate detection methods before surgery are lacking. In this study, we examined whether geneexpression profiling can predict the presence of lymph node metastasis in early stage

At the start of this project, it was known that methanogens were Archaeabacteria (now Archaea) and were therefore predicted to have geneexpression and regulatory systems different from Bacteria, but few of the molecular biology details were established. The goals were then to establish the structures and organizations of genes in methanogens, and to develop the genetic technologies needed to investigate and dissect methanogen geneexpression and regulation in vivo. By cloning and sequencing, we established the gene and operon structures of all of the “methane” genes that encode the enzymes that catalyze methane biosynthesis from carbon dioxide and hydrogen. This work identified unique sequences in the methane gene that we designated mcrA, that encodes the largest subunit of methyl-coenzyme M reductase, that could be used to identify methanogen DNA and establish methanogen phylogenetic relationships. McrA sequences are now the accepted standard and used extensively as hybridization probes to identify and quantify methanogens in environmental research. With the methane genes in hand, we used northern blot and then later whole-genome microarray hybridization analyses to establish how growth phase and substrate availability regulated methane geneexpression in Methanobacterium thermautotrophicus ΔH (now Methanothermobacter thermautotrophicus). Isoenzymes or pairs of functionally equivalent enzymes catalyze several steps in the hydrogen-dependent reduction of carbon dioxide to methane. We established that hydrogen availability determine which of these pairs of methane genes is expressed and therefore which of the alternative enzymes is employed to catalyze methane biosynthesis under different environmental conditions. As were unable to establish a reliable genetic system for M. thermautotrophicus, we developed in vitro transcription as an alternative system to investigate methanogen geneexpression and regulation. This led to the discovery that an archaeal protein

This review places modern research developments in vascular mechanobiology in the context of hemodynamic phenomena in the cardiovascular system and the discrete localization of vascular disease. The modern origins of this field are traced, beginning in the 1960s when associations between flow characteristics, particularly blood flow-induced wall shear stress, and the localization of atherosclerotic plaques were uncovered, and continuing to fluid shear stress effects on the vascular lining endothelial) cells (ECs), including their effects on EC morphology, biochemical production, and geneexpression. The earliest single-gene studies and genome-wide analyses are considered. The final section moves from the ECs lining the vessel wall to the smooth muscle cells and fibroblasts within the wall that are fluid me chanically activated by interstitial flow that imposes shear stresses on their surfaces comparable with those of flowing blood on EC surfaces. Interstitial flow stimulates biochemical production and geneexpression, much like blood flow on ECs.

Full Text Available Geneexpression profiling using microarrays has been limited to comparisons of geneexpression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000 of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "GeneExpression Commons" (https://gexc.stanford.edu/ which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the GeneExpression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.

The purpose of this study was to compare the expression profiles of drug-metabolizing enzymes in the intestine of mouse, rat and human. Total RNA was isolated from the duodenum and the mRNA expression was measured using Affymetrix GeneChip oligonucleotide arrays. Detected genes from the intestine of mouse, rat and human were ca. 60% of 22690 sequences, 40% of 8739 and 47% of 12559, respectively. Total genes of metabolizing enzymes subjected in this study were 95, 33 and 68 genes in mouse, rat and human, respectively. Of phase I enzymes, the mouse exhibited abundant geneexpressions for Cyp3a25, Cyp4v3, Cyp2d26, followed by Cyp2b20, Cyp2c65 and Cyp4f14, whereas, the rat showed higher expression profiles of Cyp3a9, Cyp2b19, Cyp4f1, Cyp17a1, Cyp2d18, Cyp27a1 and Cyp4f6. However, the highly expressed P450 enzymes were CYP3A4, CYP3A5, CYP4F3, CYP2C18, CYP2C9, CYP2D6, CYP3A7, CYP11B1 and CYP2B6 in the human. For phase II enzymes, glucuronosyltransferase Ugt1a6, glutathione S-transferases Gstp1, Gstm3 and Gsta2, sulfotransferase Sult1b1 and acyltransferase Dgat1 were highly expressed in the mouse. The rat revealed predominant expression of glucuronosyltransferases Ugt1a1 and Ugt1a7, sulfotransferase Sult1b1, acetyltransferase Dlat and acyltransferase Dgat1. On the other hand, in human, glucuronosyltransferases UGT2B15 and UGT2B17, glutathione S-transferases MGST3, GSTP1, GSTA2 and GSTM4, sulfotransferases ST1A3 and SULT1A2, acetyltransferases SAT1 and CRAT, and acyltransferase AGPAT2 were dominantly detected. Therefore, current data indicated substantial interspecies differences in the pattern of intestinal geneexpression both for P450 enzymes and phase II drug-metabolizing enzymes. This genomic database is expected to improve our understanding of interspecies variations in estimating intestinal prehepatic clearance of oral drugs.

Full Text Available Abstract Background Pneumococcal meningitis is associated with high mortality (~30% and morbidity. Up to 50% of survivors are affected by neurological sequelae due to a wide spectrum of brain injury mainly affecting the cortex and hippocampus. Despite this significant disease burden, the genetic program that regulates the host response leading to brain damage as a consequence of bacterial meningitis is largely unknown. We used an infant rat model of pneumococcal meningitis to assess geneexpression profiles in cortex and hippocampus at 22 and 44 hours after infection and in controls at 22 h after mock-infection with saline. To analyze the biological significance of the data generated by Affymetrix DNA microarrays, a bioinformatics pipeline was used combining (i a literature-profiling algorithm to cluster genes based on the vocabulary of abstracts indexed in MEDLINE (NCBI and (ii the self-organizing map (SOM, a clustering technique based on covariance in geneexpression kinetics. Results Among 598 genes differentially regulated (change factor ≥ 1.5; p ≤ 0.05, 77% were automatically assigned to one of 11 functional groups with 94% accuracy. SOM disclosed six patterns of expression kinetics. Genes associated with growth control/neuroplasticity, signal transduction, cell death/survival, cytoskeleton, and immunity were generally upregulated. In contrast, genes related to neurotransmission and lipid metabolism were transiently downregulated on the whole. The majority of the genes associated with ionic homeostasis, neurotransmission, signal transduction and lipid metabolism were differentially regulated specifically in the hippocampus. Of the cell death/survival genes found to be continuously upregulated only in hippocampus, the majority are pro-apoptotic, while those continuously upregulated only in cortex are anti-apoptotic. Conclusion Temporal and spatial analysis of geneexpression in experimental pneumococcal meningitis identified potential

Thyroglobulin is composed of two 300000 dalton polypeptide chains, translated from an 8000 base mRNA. Preparation of a full length cDNA and its cloning in E. coli have lead to the demonstration that the polypeptides of thyroglobulin protomers were identical. Used as molecular probes, the cloned cDNA allowed the isolation of a fragment of thyroglobulin gene. Electron microscopic studies have demonstrated that this gene contains more than 90 % intronic material separating small size exons (<200 bp). Sequencing of bovine thyroglobulin structural gene is in progress. Preliminary results show evidence for the existence of repetitive segments. Availability of cloned DNA complementary to bovine and human thyroglobulin mRNA allows the study of genetic defects of thyroglobulin geneexpression in the human and in various animal models.

Hypertension is a hemodynamic disorder and one of the most important and well-established risk factors for vascular diseases such as stroke. Blood vessels exposed to chronic shear stress develop structural changes and remodeling of the vascular wall through many complex mechanisms. However......, the molecular mechanisms involved are not fully understood. Hypertension-susceptible genes may provide a novel insight into potential molecular mechanisms of hypertension and secondary complications associated with hypertension. The aim of this exploratory study was to identify geneexpression differences......, the identified genes in the middle cerebral arteries from spontaneously hypertensive rats could be possible mediators of the vascular changes and secondary complications associated with hypertension. This study supports the selection of key genes to investigate in the future research of hypertension-induced end...

Full Text Available Serial analysis of geneexpression (SAGE is a powerful tool, which provides quantitative and comprehensive expression profile of genes in a given cell population. It works by isolating short fragments of genetic information from the expressedgenes that are present in the cell being studied. These short sequences, called SAGE tags, are linked together for efficient sequencing. The frequency of each SAGE tag in the cloned multimers directly reflects the transcript abundance. Therefore, SAGE results in an accurate picture of geneexpression at both the qualitative and the quantitative levels. It does not require a hybridization probe for each transcript and allows new genes to be discovered. This technique has been applied widely in human studies and various SAGE tags/SAGE libraries have been generated from different cells/tissues such as dendritic cells, lung fibroblast cells, oocytes, thyroid tissue, B-cell lymphoma, cultured keratinocytes, muscles, brain tissues, sciatic nerve, cultured Schwann cells, cord blood-derived mast cells, retina, macula, retinal pigment epithelial cells, skin cells, and so forth. In this review we present the updated information on the applications of SAGE technology mainly to human studies.

Brassica includes many successfully cultivated crop species of polyploid origin, either by ancestral genome triplication or by hybridization between two diploid progenitors, displaying complex repetitive sequences and transposons. The U's triangle, which consists of three diploids and three amphidiploids, is optimal for the analysis of complicated genomes after polyploidization. Next-generation sequencing enables the transcriptome profiling of polyploids on a global scale. We examined the geneexpression patterns of three diploids (Brassica rapa, B. nigra, and B. oleracea) and three amphidiploids (B. napus, B. juncea, and B. carinata) via digital geneexpression analysis. In total, the libraries generated between 5.7 and 6.1 million raw reads, and the clean tags of each library were mapped to 18547-21995 genes of B. rapa genome. The unambiguous tag-mapped genes in the libraries were compared. Moreover, the majority of differentially expressedgenes (DEGs) were explored among diploids as well as between diploids and amphidiploids. Gene ontological analysis was performed to functionally categorize these DEGs into different classes. The Kyoto Encyclopedia of Genes and Genomes analysis was performed to assign these DEGs into approximately 120 pathways, among which the metabolic pathway, biosynthesis of secondary metabolites, and peroxisomal pathway were enriched. The non-additive genes in Brassica amphidiploids were analyzed, and the results indicated that orthologous genes in polyploids are frequently expressed in a non-additive pattern. Methyltransferase genes showed differential expression pattern in Brassica species. Our results provided an understanding of the transcriptome complexity of natural Brassica species. The geneexpression changes in diploids and allopolyploids may help elucidate the morphological and physiological differences among Brassica species.

Full Text Available It has unambiguously been shown that genetic, environmental, demographic, and technical factors may have substantial effects on geneexpression levels. In addition to the measured variable(s of interest, there will tend to be sources of signal due to factors that are unknown, unmeasured, or too complicated to capture through simple models. We show that failing to incorporate these sources of heterogeneity into an analysis can have widespread and detrimental effects on the study. Not only can this reduce power or induce unwanted dependence across genes, but it can also introduce sources of spurious signal to many genes. This phenomenon is true even for well-designed, randomized studies. We introduce "surrogate variable analysis" (SVA to overcome the problems caused by heterogeneity in expression studies. SVA can be applied in conjunction with standard analysis techniques to accurately capture the relationship between expression and any modeled variables of interest. We apply SVA to disease class, time course, and genetics of geneexpression studies. We show that SVA increases the biological accuracy and reproducibility of analyses in genome-wide expression studies.

It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance to antimicr......It is now apparent that microorganisms undergo significant changes during the transition from planktonic to biofilm growth. These changes result in phenotypic adaptations that allow the formation of highly organized and structured sessile communities, which possess enhanced resistance...... the transition to biofilm growth, and these included genesexpressed under oxygen-limiting conditions, genes encoding (putative) transport proteins, putative oxidoreductases and genes associated with enhanced heavy metal resistance. Of particular interest was the observation that many of the genes altered...... in expression have no current defined function. These genes, as well as those induced by stresses relevant to biofilm growth such as oxygen and nutrient limitation, may be important factors that trigger enhanced resistance mechanisms of sessile communities to antibiotics and hydrodynamic shear forces....

Microarrays have become an important technology for the global analysis of geneexpression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of geneexpression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess geneexpression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in geneexpression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

Full Text Available Microarrays have become an important technology for the global analysis of geneexpression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of geneexpression arrays in plant physiology were selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess geneexpression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in geneexpression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.

This chapter reviews the study of prokaryotic geneexpression beginning with a look at the regulation of the lactose operon and the mechanism of attenuation in the tryptophan operon to the more recent development of recombinant DNA technology. The chapter deals almost entirely with escherichia coli and its bacteriophage. The only experimental technique which the authors explore in some detail is the construction and use of gene and operon fusions which have revolutionized the study of geneexpression. Various mechanisms by which E. Coli regulate the cellular levels of individual messenger-RNA species are described. Translational regulation of the cellular levels of messenger-RNA include signals encoded within the messenger-RNA molecule itself and regulatory molecules which interact with the messenger-RNA and alter it translational efficiency

Full Text Available Drosophila segmentation as a model organism is one of the most highly studied. Among many maternal segmentation coordinate genes, bicoid protein pattern plays a significant role during Drosophila embryogenesis, since this gradient determines most aspects of head and thorax development. Despite the fact that several models have been proposed to describe the bicoid gradient, due to its association with considerable error, each can only partially explain bicoid characteristics. In this paper, a modified version of singular spectrum analysis is examined for filtering and extracting the bicoid geneexpression signal. The results with strong evidence indicate that the proposed technique is able to remove noise more effectively and can be considered as a promising method for filtering geneexpression measurements for other applications.

model to investigate the role of telomerase in AML, we were able to translate the observed effect into human AML patients and identify specific genes involved, which also predict survival patterns in AML patients. During these studies we have applied methods for investigating differentially expressed......-based gene-lookup webservices, called HemaExplorer and BloodSpot. These web-services support the aim of making data and analysis of haematopoietic cells from mouse and human accessible for researchers without bioinformatics expertise. Finally, in order to aid the analysis of the very limited number...

Based on a literature review and analysis of teaching methods and objectives, it is proposed that the emphasis on communicative competence ascendant in French foreign language instruction is closely related to, and borrows from, expressivetechniques taught in French native language instruction in the 1960s. (MSE)

Full Text Available Abstract Background The bacterium Pseudomonas aeruginosa is capable of three types of motilities: swimming, twitching and swarming. The latter is characterized by a fast and coordinated group movement over a semi-solid surface resulting from intercellular interactions and morphological differentiation. A striking feature of swarming motility is the complex fractal-like patterns displayed by migrating bacteria while they move away from their inoculation point. This type of group behaviour is still poorly understood and its characterization provides important information on bacterial structured communities such as biofilms. Using GeneChip® Affymetrix microarrays, we obtained the transcriptomic profiles of both bacterial populations located at the tip of migrating tendrils and swarm center of swarming colonies and compared these profiles to that of a bacterial control population grown on the same media but solidified to not allow swarming motility. Results Microarray raw data were corrected for background noise with the RMA algorithm and quantile normalized. Differentially expressedgenes between the three conditions were selected using a threshold of 1.5 log2-fold, which gave a total of 378 selected genes (6.3% of the predicted open reading frames of strain PA14. Major shifts in geneexpression patterns are observed in each growth conditions, highlighting the presence of distinct bacterial subpopulations within a swarming colony (tendril tips vs. swarm center. Unexpectedly, microarrays expression data reveal that a minority of genes are up-regulated in tendril tip populations. Among them, we found energy metabolism, ribosomal protein and transport of small molecules related genes. On the other hand, many well-known virulence factors genes were globally repressed in tendril tip cells. Swarm center cells are distinct and appear to be under oxidative and copper stress responses. Conclusions Results reported in this study show that, as opposed to

Full Text Available Representing and analyzing complex networks remains a roadblock to creating dynamic network models of biological processes and pathways. The study of cell fate transitions can reveal much about the transcriptional regulatory programs that underlie these phenotypic changes and give rise to the coordinated patterns in expression changes that we observe. The application of geneexpression state space trajectories to capture cell fate transitions at the genome-wide level is one approach currently used in the literature. In this paper, we analyze the geneexpression dataset of Huang et al. (2005 which follows the differentiation of promyelocytes into neutrophil-like cells in the presence of inducers dimethyl sulfoxide and all-trans retinoic acid. Huang et al. (2005 build on the work of Kauffman (2004 who raised the attractor hypothesis, stating that cells exist in an expression landscape and their expression trajectories converge towards attractive sites in this landscape. We propose an alternative interpretation that explains this convergent behavior by recognizing that there are two types of processes participating in these cell fate transitions-core processes that include the specific differentiation pathways of promyelocytes to neutrophils, and transient processes that capture those pathways and responses specific to the inducer. Using functional enrichment analyses, specific biological examples and an analysis of the trajectories and their core and transient components we provide a validation of our hypothesis using the Huang et al. (2005 dataset.

Full Text Available Purpose: Gastric cancer has high incidence and mortality rate in several countries and is still one of the most frequent and lethal disease. In this study, we aimed to determine diagnostic markers in gastric cancer by molecular techniques; include mRNA expression analysis of FABP4 gene. Fatty acid binding protein 4 (FABP4 gene encodes the fatty acid binding protein found in adipocytes. The protein encoded by FABP4 are a family of small, highly conserved, cytoplasmic proteins that bind long-chain fatty acids and other hydrophobic ligands. It is thought that FABPs roles include fatty acid uptake, transport, and metabolism. Material and Methods: Total RNA were extracted from paired tumor and normal tissues of 47 gastric cancer. The mRNA expression level of FABP4 was measured employing semi- quantitative reverse transcription- polymerase chain reaction (RT- PCR. Results: The mRNA expression level of FABP4 was significantly decreased (down- regulated. Conclusion: Down-regulation of FABP4 gene seems to occur at the initial steps of gastric cancer development. In order to confirm the relationship between the gastric tumor and FABP4 gene, further analysis like immunohistochemistry and epigenetc techniques are necessary. [Cukurova Med J 2016; 41(2.000: 248-252

Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on geneexpression, without explicit discrimination between global expression differences and tissue

Full Text Available Bronchiolitis obliterans syndrome (BOS, the main manifestation of chronic lung allograft dysfunction, leads to poor long-term survival after lung transplantation. Identifying predictors of BOS is essential to prevent the progression of dysfunction before irreversible damage occurs. By using a large set of 107 samples from lung recipients, we performed microarray geneexpression profiling of whole blood to identify early biomarkers of BOS, including samples from 49 patients with stable function for at least 3 years, 32 samples collected at least 6 months before BOS diagnosis (prediction group, and 26 samples at or after BOS diagnosis (diagnosis group. An independent set from 25 lung recipients was used for validation by quantitative PCR (13 stables, 11 in the prediction group, and 8 in the diagnosis group. We identified 50 transcripts differentially expressed between stable and BOS recipients. Three genes, namely POU class 2 associating factor 1 (POU2AF1, T-cell leukemia/lymphoma protein 1A (TCL1A, and B cell lymphocyte kinase, were validated as predictive biomarkers of BOS more than 6 months before diagnosis, with areas under the curve of 0.83, 0.77, and 0.78 respectively. These genes allow stratification based on BOS risk (log-rank test p gene expression analysis of blood after lung transplantation. The three-gene blood signature could provide clinicians with new tools to improve follow-up and adapt treatment of patients likely to develop BOS.

Full Text Available Abstract Background Serial Analysis of GeneExpression (SAGE is a new technique that allows a detailed and profound quantitative and qualitative knowledge of geneexpression profile, without previous knowledge of sequence of analyzed genes. We carried out a modification of SAGE methodology (microSAGE, useful for the analysis of limited quantities of tissue samples, on normal human cervical tissue obtained from a donor without histopathological lesions. Cervical epithelium is constituted mainly by cervical keratinocytes which are the targets of human papilloma virus (HPV, where persistent HPV infection of cervical epithelium is associated with an increase risk for developing cervical carcinomas (CC. Results We report here a transcriptome analysis of cervical tissue by SAGE, derived from 30,418 sequenced tags that provide a wealth of information about the gene products involved in normal cervical epithelium physiology, as well as genes not previously found in uterine cervix tissue involved in the process of epidermal differentiation. Conclusion This first comprehensive and profound analysis of uterine cervix transcriptome, should be useful for the identification of genes involved in normal cervix uterine function, and candidate genes associated with cervical carcinoma.

Autographa californica multiple nucleopolyhedrovirus ORF34 is part of a transcriptional unit that includes ORF32, encoding a viral fibroblast growth factor (FGF) and ORF33. We identified ORF34 as a candidate for deletion to improve protein expression in the baculovirus expression system based on enhanced reporter geneexpression in an RNAi screen of virus genes. However, ORF34 was shown to be an essential gene. To explore ORF34 function, deletion (KO34) and rescue bacmids were constructed and characterized. Infection did not spread from primary KO34 transfected cells and supernatants from KO34 transfected cells could not infect fresh Sf21 cells whereas the supernatant from the rescue bacmids transfection could recover the infection. In addition, budded viruses were not observed in KO34 transfected cells by electron microscopy, nor were viral proteins detected from the transfection supernatants by western blots. These demonstrate that ORF34 is an essential gene with a possible role in infectious virus production.

Autographa californica multiple nucleopolyhedrovirus ORF34 is part of a transcriptional unit that includes ORF32, encoding a viral fibroblast growth factor (FGF) and ORF33. We identified ORF34 as a candidate for deletion to improve protein expression in the baculovirus expression system based on enhanced reporter geneexpression in an RNAi screen of virus genes. However, ORF34 was shown to be an essential gene. To explore ORF34 function, deletion (KO34) and rescue bacmids were constructed and characterized. Infection did not spread from primary KO34 transfected cells and supernatants from KO34 transfected cells could not infect fresh Sf21 cells whereas the supernatant from the rescue bacmids transfection could recover the infection. In addition, budded viruses were not observed in KO34 transfected cells by electron microscopy, nor were viral proteins detected from the transfection supernatants by western blots. These demonstrate that ORF34 is an essential gene with a possible role in infectious virus production.

"In situ" hybridization is a widely used technique for studying geneexpression. Here, we describe two experiments addressed to postgraduate genetics students in which the effect of transcription factors on geneexpression is analyzed in "Drosophila embryos of different genotypes by whole-mount in situ hybridization. In one of the…

Our understanding of the mechanisms controlling insect diapause has increased dramatically with the introduction of global geneexpressiontechniques, such as RNAseq. However, little attention has been given to how ecologically relevant field conditions may affect geneexpression during diapause dev...

We have obtained a promoter enhancing expression of a gene of our interest connected downstream after activation in response to radiation stimulation and it could be used in radiogenetic therapy, a combination between radiotherapy and gene therapy. The promoter has been chosen out of a library of DNA fragments constructed by connecting the TATA box to randomly combined binding sequences of transcription factors that are activated in response to radiation. Although it was shown that the promoter activation was cell type specific, it turned out that radiation responsive promoters could be obtained for a different type of cells by using another set of transcription factor binding sequences, suggesting that the method would be feasible to obtain promoters functioning in any type of cells. Radiation reactivity of obtained promoters could be improved by techniques such as random introduction of point mutations. The improved promoters significantly enhanced expression of the luciferase gene connected downstream in response to radiation even in vivo, in addition, a gene cassette composed of one such promoter and the fcy::fur gene was confirmed useful for suicide gene therapy as shown in vitro simulation experiment, suggesting possible clinical application. (author)

Full Text Available Abstract Xeroderma pigmentosum (XP is a rare recessive disorder that is characterized by extreme sensitivity to UV light. UV light exposure results in the formation of DNA damage such as cyclobutane dimers and (6-4 photoproducts. Nucleotide excision repair (NER orchestrates the removal of cyclobutane dimers and (6-4 photoproducts as well as some forms of bulky chemical DNA adducts. The disease XP is comprised of 7 complementation groups (XP-A to XP-G, which represent functional deficiencies in seven different genes, all of which are believed to be involved in NER. The main clinical feature of XP is various forms of skin cancers; however, neurological degeneration is present in XPA, XPB, XPD and XPG complementation groups. The relationship between NER and other types of DNA repair processes is now becoming evident but the exact relationships between the different complementation groups remains to be precisely determined. Using geneexpression analysis we have identified similarities and differences after UV light exposure between the complementation groups XP-A, XP-C, XP-D, XP-E, XP-F, XP-G and an unaffected control. The results reveal that there is a graded change in geneexpression patterns between the mildest, most similar to the control response (XP-E and the severest form (XP-A of the disease, with the exception of XP-D. Distinct differences between the complementation groups with neurological symptoms (XP-A, XP-D and XP-G and without (XP-C, XP-E and XP-F were also identified. Therefore, this analysis has revealed distinct geneexpression profiles for the XP complementation groups and the first step towards understanding the neurological symptoms of XP.

of geneexpression in the ventral prostate, it is not clear whether all the geneexpression ... These include clusterin, methionine adenosyl transferase IIα, and prostate-specific ..... MAGEE1 melanoma antigen and no similarity was found with the ...

Introduction: Progress with gene-based therapies has been hampered by difficulties in monitoring the biodistribution and kinetics of vector-mediated geneexpression. Recent developments in non-invasive imaging have allowed researchers and clinicians to assess the location, magnitude and persistence of geneexpression in animals and humans. Such advances should eventually lead to improvement in the efficacy and safety of current clinical protocols for future treatments. Areas Covered: The molecular imaging techniques for monitoring gene therapy in the living subject, with a specific highlight on the key reporter gene approaches that have been developed and validated in preclinical models using the latest imaging modalities. The applications of molecular imaging to biotherapy, with a particular emphasis on monitoring of gene and vector biodistribution and on image-guided radiotherapy. Expert Opinion: Among the reporter gene/probe combinations that have been described so far, one stands out, in our view, as the most versatile and easy to implement: the Na/I symporter. This strategy, exploiting more than 50 years of experience in the treatment of differentiated thyroid carcinomas, has been validated in different types of experimental cancers and with different types of oncolytic viruses and is likely to become a key tool in the implementation of human gene therapy. (authors)

Full Text Available Abstract Background There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many instances the biologically important goal is to identify relatively small sets of genes that share coherent expression across only some conditions, rather than all or most conditions as required in traditional clustering; e.g. genes that are highly up-regulated and/or down-regulated similarly across only a subset of conditions. Equally important is the need to learn which conditions are the decisive ones in forming such gene sets of interest, and how they relate to diverse conditional covariates, such as disease diagnosis or prognosis. Results We present a method for automatically identifying such candidate sets of biologically relevant genes using a combination of principal components analysis and information theoretic metrics. To enable easy use of our methods, we have developed a data analysis package that facilitates visualization and subsequent data mining of the independent sources of significant variation present in gene microarray expression datasets (or in any other similarly structured high-dimensional dataset. We applied these tools to two public datasets, and highlight sets of genes most affected by specific subsets of conditions (e.g. tissues, treatments, samples, etc.. Statistically significant associations for highlighted gene sets were shown via global analysis for Gene Ontology term enrichment. Together with covariate associations, the tool provides a basis for building testable hypotheses about the biological or experimental causes of observed variation. Conclusion We provide an unsupervised data mining technique for diverse microarray expression datasets that is distinct from major methods now in routine use. In test uses, this method, based on publicly available gene annotations, appears to identify numerous sets of biologically relevant genes. It

Highlights: •AXIN2 localizes to cytoplasmic and nuclear compartments in colorectal cancer cells. •Nuclear AXIN2 represses the activity of Wnt-responsive luciferase reporters. •β-Catenin bridges AXIN2 to TCF transcription factors. •AXIN2 binds the MYC promoter and represses MYC geneexpression. -- Abstract: The β-catenin transcriptional coactivator is the key mediator of the canonical Wnt signaling pathway. In the absence of Wnt, β-catenin associates with a cytosolic and multi-protein destruction complex where it is phosphorylated and targeted for proteasomal degradation. In the presence of Wnt, the destruction complex is inactivated and β-catenin translocates into the nucleus. In the nucleus, β-catenin binds T-cell factor (TCF) transcription factors to activate expression of c-MYC (MYC) and Axis inhibition protein 2 (AXIN2). AXIN2 is a member of the destruction complex and, thus, serves in a negative feedback loop to control Wnt/β-catenin signaling. AXIN2 is also present in the nucleus, but its function within this compartment is unknown. Here, we demonstrate that AXIN2 localizes to the nuclei of epithelial cells within normal and colonic tumor tissues as well as colorectal cancer cell lines. In the nucleus, AXIN2 represses expression of Wnt/β-catenin-responsive luciferase reporters and forms a complex with β-catenin and TCF. We demonstrate that AXIN2 co-occupies β-catenin/TCF complexes at the MYC promoter region. When constitutively localized to the nucleus, AXIN2 alters the chromatin structure at the MYC promoter and directly represses MYC geneexpression. These findings suggest that nuclear AXIN2 functions as a rheostat to control MYC expression in response to Wnt/β-catenin signaling.

Highlights: •AXIN2 localizes to cytoplasmic and nuclear compartments in colorectal cancer cells. •Nuclear AXIN2 represses the activity of Wnt-responsive luciferase reporters. •β-Catenin bridges AXIN2 to TCF transcription factors. •AXIN2 binds the MYC promoter and represses MYC geneexpression. -- Abstract: The β-catenin transcriptional coactivator is the key mediator of the canonical Wnt signaling pathway. In the absence of Wnt, β-catenin associates with a cytosolic and multi-protein destruction complex where it is phosphorylated and targeted for proteasomal degradation. In the presence of Wnt, the destruction complex is inactivated and β-catenin translocates into the nucleus. In the nucleus, β-catenin binds T-cell factor (TCF) transcription factors to activate expression of c-MYC (MYC) and Axis inhibition protein 2 (AXIN2). AXIN2 is a member of the destruction complex and, thus, serves in a negative feedback loop to control Wnt/β-catenin signaling. AXIN2 is also present in the nucleus, but its function within this compartment is unknown. Here, we demonstrate that AXIN2 localizes to the nuclei of epithelial cells within normal and colonic tumor tissues as well as colorectal cancer cell lines. In the nucleus, AXIN2 represses expression of Wnt/β-catenin-responsive luciferase reporters and forms a complex with β-catenin and TCF. We demonstrate that AXIN2 co-occupies β-catenin/TCF complexes at the MYC promoter region. When constitutively localized to the nucleus, AXIN2 alters the chromatin structure at the MYC promoter and directly represses MYC geneexpression. These findings suggest that nuclear AXIN2 functions as a rheostat to control MYC expression in response to Wnt/β-catenin signaling

Full Text Available Organisms simplify the orchestration of geneexpression by coregulating genes whose products function together in the cell. The use of clustering methods to obtain sets of coexpressed genes from expression arrays is very common; nevertheless there are no appropriate tools to study the expression networks among these sets of coexpressed genes. The aim of the developed tools is to allow studying the complex expression dependences that exist between sets of coexpressed genes. For this purpose, we start detecting the nonlinear expression relationships between pairs of genes, plus the coexpressed genes. Next, we form networks among sets of coexpressed genes that maintain nonlinear expression dependences between all of them. The expression relationship between the sets of coexpressed genes is defined by the expression relationship between the skeletons of these sets, where this skeleton represents the coexpressed genes with a well-defined nonlinear expression relationship with the skeleton of the other sets. As a result, we can study the nonlinear expression relationships between a target gene and other sets of coexpressed genes, or start the study from the skeleton of the sets, to study the complex relationships of activation and deactivation between the sets of coexpressed genes that carry out the different cellular processes present in the expression experiments.

Full Text Available Abstract Background The ability to monitor the change in expression patterns over time, and to observe the emergence of coherent temporal responses using geneexpression time series, obtained from microarray experiments, is critical to advance our understanding of complex biological processes. In this context, biclustering algorithms have been recognized as an important tool for the discovery of local expression patterns, which are crucial to unravel potential regulatory mechanisms. Although most formulations of the biclustering problem are NP-hard, when working with time series expression data the interesting biclusters can be restricted to those with contiguous columns. This restriction leads to a tractable problem and enables the design of efficient biclustering algorithms able to identify all maximal contiguous column coherent biclusters. Methods In this work, we propose e-CCC-Biclustering, a biclustering algorithm that finds and reports all maximal contiguous column coherent biclusters with approximate expression patterns in time polynomial in the size of the time series geneexpression matrix. This polynomial time complexity is achieved by manipulating a discretized version of the original matrix using efficient string processing techniques. We also propose extensions to deal with missing values, discover anticorrelated and scaled expression patterns, and different ways to compute the errors allowed in the expression patterns. We propose a scoring criterion combining the statistical significance of expression patterns with a similarity measure between overlapping biclusters. Results We present results in real data showing the effectiveness of e-CCC-Biclustering and its relevance in the discovery of regulatory modules describing the transcriptomic expression patterns occurring in Saccharomyces cerevisiae in response to heat stress. In particular, the results show the advantage of considering approximate patterns when compared to state of

Full Text Available The understanding of selective constraints affecting genes is a major issue in biology. It is well established that geneexpression level is a major determinant of the rate of protein evolution, but the reasons for this relationship remain highly debated. Here we demonstrate that geneexpression is also a major determinant of the evolution of gene dosage: the rate of gene losses after whole genome duplications in the Paramecium lineage is negatively correlated to the level of geneexpression, and this relationship is not a byproduct of other factors known to affect the fate of gene duplicates. This indicates that changes in gene dosage are generally more deleterious for highly expressedgenes. This rule also holds for other taxa: in yeast, we find a clear relationship between geneexpression level and the fitness impact of reduction in gene dosage. To explain these observations, we propose a model based on the fact that the optimal expression level of a gene corresponds to a trade-off between the benefit and cost of its expression. This COSTEX model predicts that selective pressure against mutations changing geneexpression level or affecting the encoded protein should on average be stronger in highly expressedgenes and hence that both the frequency of gene loss and the rate of protein evolution should correlate negatively with geneexpression. Thus, the COSTEX model provides a simple and common explanation for the general relationship observed between the level of geneexpression and the different facets of gene evolution.

Full Text Available Classification of cancer based on geneexpression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM, bagging, and random forest on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and geneexpression increase the prediction accuracy as compared to using geneexpression alone.

Digital geneexpression (DGE) profiling techniques are playing an eminent role in the detection, localization, and differential expression quantification of many small RNA species, including microRNAs (1-3). Procedures in small RNA library preparation techniques typically include adapter ligation by

Full Text Available Abstract Background Although the sequence of events leading to wound repair has been described at the cellular and, to a limited extent, at the protein level this process has yet to be fully elucidated. Genome wide transcriptional analysis tools promise to further define the global picture of this complex progression of events. Study Design This study was part of a placebo-controlled double-blind clinical trial in which basal cell carcinomas were treated topically with an immunomodifier – toll-like receptor 7 agonist: imiquimod. The fourteen patients with basal cell carcinoma in the placebo arm of the trial received placebo treatment consisting solely of vehicle cream. A skin punch biopsy was obtained immediately before treatment and at the end of the placebo treatment (after 2, 4 or 8 days. 17.5K cDNA microarrays were utilized to profile the biopsy material. Results Four gene signatures whose expression changed relative to baseline (before wound induction by the pre-treatment biopsy were identified. The largest group was comprised predominantly of inflammatory genes whose expression was increased throughout the study. Two additional signatures were observed which included preferentially pro-inflammatory genes in the early post-treatment biopsies (2 days after pre-treatment biopsies and repair and angiogenesis genes in the later (4 to 8 days biopsies. The fourth and smallest set of genes was down-regulated throughout the study. Early in wound healing the expression of markers of both M1 and M2 macrophages were increased, but later M2 markers predominated. Conclusion The initial response to a cutaneous wound induces powerful transcriptional activation of pro-inflammatory stimuli which may alert the host defense. Subsequently and in the absence of infection, inflammation subsides and it is replaced by angiogenesis and remodeling. Understanding this transition which may be driven by a change from a mixed macrophage population to predominately M2

that compare cells grown in suspension to similar cells grown attached to one another as aggregates have suggested that it is adhesion to the extracellular matrix of the basal membrane that confers resistance to apoptosis and, hence, resistance to cytotoxins. The genes whose expression correlates with poor...... in cell adhesion and the cytoskeleton. If the proteins involved in tethering cells to the extracellular matrix are important in conferring drug resistance, it may be possible to improve chemotherapy by designing drugs that target these proteins....

Full Text Available We tackle the problem of completing and inferring genetic networks under stationary conditions from static data, where network completion is to make the minimum amount of modifications to an initial network so that the completed network is most consistent with the expression data in which addition of edges and deletion of edges are basic modification operations. For this problem, we present a new method for network completion using dynamic programming and least-squares fitting. This method can find an optimal solution in polynomial time if the maximum indegree of the network is bounded by a constant. We evaluate the effectiveness of our method through computational experiments using synthetic data. Furthermore, we demonstrate that our proposed method can distinguish the differences between two types of genetic networks under stationary conditions from lung cancer and normal geneexpression data.

Full Text Available Abstract Background Temporal geneexpression profiles characterize the time-dynamics of expression of specific genes and are increasingly collected in current geneexpression experiments. In the analysis of experiments where geneexpression is obtained over the life cycle, it is of interest to relate temporal patterns of geneexpression associated with different developmental stages to each other to study patterns of long-term developmental gene regulation. We use tools from functional data analysis to study dynamic changes by relating temporal geneexpression profiles of different developmental stages to each other. Results We demonstrate that functional regression methodology can pinpoint relationships that exist between temporary geneexpression profiles for different life cycle phases and incorporates dimension reduction as needed for these high-dimensional data. By applying these tools, geneexpression profiles for pupa and adult phases are found to be strongly related to the profiles of the same genes obtained during the embryo phase. Moreover, one can distinguish between gene groups that exhibit relationships with positive and others with negative associations between later life and embryonal expression profiles. Specifically, we find a positive relationship in expression for muscle development related genes, and a negative relationship for strictly maternal genes for Drosophila, using temporal geneexpression profiles. Conclusion Our findings point to specific reactivation patterns of geneexpression during the Drosophila life cycle which differ in characteristic ways between various gene groups. Functional regression emerges as a useful tool for relating geneexpression patterns from different developmental stages, and avoids the problems with large numbers of parameters and multiple testing that affect alternative approaches.

We used the nematode C. elegans to characterize the genotoxic and cytotoxic effects of ionizing radiation in a simple animal model emphasizing the unique effects of charged particle radiation. Here we demonstrate by reverse transcription polymerase chain reaction (RT-PCR) differential display and whole genome microarray hybridization experiments that gamma rays, accelerated protons and iron ions at the same physical dose lead to unique transcription profiles. 599 of 17871 genes analyzed (3.4%) showed differential expression 3 hrs after exposure to 3 Gy of radiation. 193 were up-regulated, 406 were down-regulated and 90% were affected only by a single species of radiation. A novel statistical clustering technique identified the regulatory relationships between the radiation-modulated genes and showed that genes affected by each radiation species were associated with unique regulatory clusters. This suggests that independent homeostatic mechanisms are activated in response to radiation exposure as a function of track structure or ionization density. (author)

The development and application of radiopharmaceuticals has, in many instances, been based on the pharmacological properties of therapeutic agents. The molecular biology-biotechnology revolution has had an important impact on treatment of diseases, in part through the reduced toxicity of 'biologicals', in part because of their specificity for interaction at unique molecular sites and in part because of their selective delivery to the target site. Immunotherapeutic approaches include the use of monoclonal antibodies (MABs), MAB-fragments and chemotactic peptides. Such agents currently form the basis of both diagnostic and immunotherapeutic radiopharmaceuticals. More recently, gene transfer techniques have been advanced to the point that a new molecular approach, gene therapy, has become a reality. Gene therapy offers an opportunity to attack disease at its most fundamental level. The therapeutic mechanism is based on the expression of a specific gene or genes, the product of which will invoke immunological, receptor-based or enzyme-based therapeutic modalities. Several approaches to gene therapy of cancer have been envisioned, the most clinically-advanced concepts involving the introduction of genes that will encode for molecular targets nor normally found in healthy mammalian cells. A number of gene therapy clinical trials are based on the introduction of the Herpes simplex virus type-1 (HSV-1) gene that encodes for viral thymidine kinase (tk+). Once HSV-1 tk+ is expressed in the target (cancer) cell, therapy can be effected by the administration of a highly molecularly-targeted and systemically non-toxic antiviral drug such as ganciclovir. The development of radiodiagnostic imaging in gene therapy will be reviewed, using HSV-1 tk+ and radioiodinated IVFRU as a basis for development of the theme. Molecular targets that could be exploited in gene therapy, other than tk+, will be identified

The development and application of radiopharmaceuticals has, in many instances, been based on the pharmacological properties of therapeutic agents. The molecular biology-biotechnology revolution has had an important impact on treatment of diseases, in part through the reduced toxicity of `biologicals`, in part because of their specificity for interaction at unique molecular sites and in part because of their selective delivery to the target site. Immunotherapeutic approaches include the use of monoclonal antibodies (MABs), MAB-fragments and chemotactic peptides. Such agents currently form the basis of both diagnostic and immunotherapeutic radiopharmaceuticals. More recently, gene transfer techniques have been advanced to the point that a new molecular approach, gene therapy, has become a reality. Gene therapy offers an opportunity to attack disease at its most fundamental level. The therapeutic mechanism is based on the expression of a specific gene or genes, the product of which will invoke immunological, receptor-based or enzyme-based therapeutic modalities. Several approaches to gene therapy of cancer have been envisioned, the most clinically-advanced concepts involving the introduction of genes that will encode for molecular targets nor normally found in healthy mammalian cells. A number of gene therapy clinical trials are based on the introduction of the Herpes simplex virus type-1 (HSV-1) gene that encodes for viral thymidine kinase (tk+). Once HSV-1 tk+ is expressed in the target (cancer) cell, therapy can be effected by the administration of a highly molecularly-targeted and systemically non-toxic antiviral drug such as ganciclovir. The development of radiodiagnostic imaging in gene therapy will be reviewed, using HSV-1 tk+ and radioiodinated IVFRU as a basis for development of the theme. Molecular targets that could be exploited in gene therapy, other than tk+, will be identified

Background Since the development of transcriptome analysis systems, many expression evolution studies characterized evolutionary forces acting on geneexpression, without explicit discrimination between global expression differences and tissue specific expression differences. However, different types of geneexpression alteration should have different effects on an organism, the evolutionary forces that act on them might be different, and different types of genes might show different types of differential expression between species. To confirm this, we studied differentially expressed (DE) genes among closely related groups that have extensive geneexpression atlases, and clarified characteristics of different types of DE genes including the identification of regulating loci for differential expression using expression quantitative loci (eQTL) analysis data. Results We detected differentially expressed (DE) genes between rice subspecies in five homologous tissues that were verified using japonica and indica transcriptome atlases in public databases. Using the transcriptome atlases, we classified DE genes into two types, global DE genes and changed-tissues DE genes. Global type DE genes were not expressed in any tissues in the atlas of one subspecies, however changed-tissues type DE genes were expressed in both subspecies with different tissue specificity. For the five tissues in the two japonica-indica combinations, 4.6 ± 0.8 and 5.9 ± 1.5 % of highly expressedgenes were global and changed-tissues DE genes, respectively. Changed-tissues DE genes varied in number between tissues, increasing linearly with the abundance of tissue specifically expressedgenes in the tissue. Molecular evolution of global DE genes was rapid, unlike that of changed-tissues DE genes. Based on gene ontology, global and changed-tissues DE genes were different, having no common GO terms. Expression differences of most global DE genes were regulated by cis-eQTLs. Expression

We present GENeVis, an application to visualize geneexpression time series data in a gene regulatory network context. This is a network of regulator proteins that regulate the expression of their respective target genes. The networks are represented as graphs, in which the nodes represent genes,

Full Text Available Abstract Background Gene therapy continues to hold great potential for treating many different types of disease and dysfunction. Safe and efficient techniques for gene transfer and expression in vivo are needed to enable gene therapeutic strategies to be effective in patients. Currently, the most commonly used methods employ replication-defective viral vectors for gene transfer, while physical gene transfer methods such as biolistic-mediated ("gene-gun" delivery to target tissues have not been as extensively explored. In the present study, we evaluated the efficacy of biolistic gene transfer techniques in vivo using non-invasive bioluminescent imaging (BLI methods. Results Plasmid DNA carrying the firefly luciferase (LUC reporter gene under the control of the human Cytomegalovirus (CMV promoter/enhancer was transfected into mouse skin and liver using biolistic methods. The plasmids were coupled to gold microspheres (1 μm diameter using different DNA Loading Ratios (DLRs, and "shot" into target tissues using a helium-driven gene gun. The optimal DLR was found to be in the range of 4-10. Bioluminescence was measured using an In Vivo Imaging System (IVIS-50 at various time-points following transfer. Biolistic gene transfer to mouse skin produced peak reporter geneexpression one day after transfer. Expression remained detectable through four days, but declined to undetectable levels by six days following gene transfer. Maximum depth of tissue penetration following biolistic transfer to abdominal skin was 200-300 μm. Similarly, biolistic gene transfer to mouse liver in vivo also produced peak early expression followed by a decline over time. In contrast to skin, however, liver expression of the reporter gene was relatively stable 4-8 days post-biolistic gene transfer, and remained detectable for nearly two weeks. Conclusions The use of bioluminescence imaging techniques enabled efficient evaluation of reporter geneexpression in vivo. Our results

Recent work has shown that the expression levels of genes transcribed in the brains of humans and chimpanzees have changed less than those of genes transcribed in other tissues [1] . However, when geneexpression changes are mapped onto the evolutionary lineage in which they occurred, the brain...... shows more changes than other tissues in the human lineage compared to the chimpanzee lineage [1] , [2] and [3] . There are two possible explanations for this: either positive selection drove more geneexpression changes to fixation in the human brain than in the chimpanzee brain, or genesexpressed...... in the brain experienced less purifying selection in humans than in chimpanzees, i.e. geneexpression in the human brain is functionally less constrained. The first scenario would be supported if genes that changed their expression in the brain in the human lineage showed more selective sweeps than other genes...

The regulation of geneexpression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the geneexpression pattern from three directions: 1) expression breadth, which reflects geneexpression on/off status, and mainly concerns ubiquitously expressedgenes; 2) low/high or constant/variable expressiongenes, based on geneexpression level and variation; and 3) the regulation of geneexpression at the gene structure level. The cluster analysis indicates that geneexpression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the geneexpression pattern in geneexpression level and variation, we firstly apply improved K-means algorithm and a geneexpression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of geneexpression differ among different cell types, and particularly for cancer. PMID:23382867

Full Text Available Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the geneexpression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate.

Differentiation between malignant renal cell carcinoma and benign oncocytoma is of great importance to choose the optimal treatment. Accurate preoperative diagnosis of renal tumor is therefore crucial; however, existing imaging techniques and histologic examinations are incapable of providing an optimal differentiation profile. Analysis of geneexpression of molecular markers is a new possibility but relies on appropriate standardization to compare different samples. The aim of this study was to identify stably expressed reference genes suitable for the normalization of results extracted from geneexpression analysis of renal tumors. Expression levels of 8 potential reference genes (ATP5J, HMBS, HPRT1, PPIA, TBP, 18S, GAPDH, and POLR2A) were examined by real-time reverse transcription polymerase chain reaction in tumor and normal tissue from removed kidneys from 13 patients with renal cell carcinoma and 5 patients with oncocytoma. The expression levels of genes were compared by gene stability value M, average gene stability M, pairwise variation V, and coefficient of variation CV. More candidates were not suitable for the purpose, but a combination of HMBS, PPIA, ATP5J, and TBP was found to be the best combination with an average gene stability value M of 0.9 and a CV of 0.4 in the 18 tumors and normal tissues. A combination of 4 genes, HMBS, PPIA, ATP5J, and TBP, is a possible reference in renal tumor geneexpression analysis by reverse transcription polymerase chain reaction. A combination of four genes, HMBS, PPIA, ATP5J and TBP, being stably expressed in tissues from RCC is possible reference genes for geneexpression analysis.

Geneexpression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between geneexpression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged geneexpression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the geneexpression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of geneexpression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar geneexpression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental

Full Text Available Abstract Background Geneexpression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between geneexpression maps obtained by voxelation and gene functions. Results To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged geneexpression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the geneexpression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of geneexpression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar geneexpression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in

In this review, we present an overview of transcriptomic responses to chemical exposures in a variety of fish species. We have discussed the use of several molecular approaches such as northern blotting, differential display reverse transcription-polymerase chain reaction (DDRT-PCR), suppression subtractive hybridization (SSH), real time quantitative PCR (RT-qPCR), microarrays, and next-generation sequencing (NGS) for measuring geneexpression. These techniques have been mainly used to measure the toxic effects of single compounds or simple mixtures in laboratory conditions. In addition, only few studies have been conducted to examine the biological significance of differentially expressedgene sets following chemical exposure. Therefore, future studies should focus more under field conditions using a multidisciplinary approach (genomics, proteomics and metabolomics) to understand the synergetic effects of multiple environmental stressors and to determine the functional significance of differentially expressedgenes. Nevertheless, recent developments in NGS technologies and decreasing costs of sequencing holds the promise to uncover the complexity of anthropogenic impacts and biological effects in wild fish populations.

Full Text Available Abstract Background The increasing number of geneexpression microarray studies represents an important resource in biomedical research. As a result, geneexpression based diagnosis has entered clinical practice for patient stratification in breast cancer. However, the integration and combined analysis of microarray studies remains still a challenge. We assessed the potential benefit of data integration on the classification accuracy and systematically evaluated the generalization performance of selected methods on four breast cancer studies comprising almost 1000 independent samples. To this end, we introduced an evaluation framework which aims to establish good statistical practice and a graphical way to monitor differences. The classification goal was to correctly predict estrogen receptor status (negative/positive and histological grade (low/high of each tumor sample in an independent study which was not used for the training. For the classification we chose support vector machines (SVM, predictive analysis of microarrays (PAM, random forest (RF and k-top scoring pairs (kTSP. Guided by considerations relevant for classification across studies we developed a generalization of kTSP which we evaluated in addition. Our derived version (DV aims to improve the robustness of the intrinsic invariance of kTSP with respect to technologies and preprocessing. Results For each individual study the generalization error was benchmarked via complete cross-validation and was found to be similar for all classification methods. The misclassification rates were substantially higher in classification across studies, when each single study was used as an independent test set while all remaining studies were combined for the training of the classifier. However, with increasing number of independent microarray studies used in the training, the overall classification performance improved. DV performed better than the average and showed slightly less variance. In

Highly expressedgenes in any species differ in the usage frequency of synonymous codons. The relative recurrence of an event of the favored codon pair (amino acid pairs) varies between gene and genomes due to varying geneexpression and different base composition. Here we propose a new measure for predicting the geneexpression level, i.e., codon plus amino bias index (CABI). Our approach is based on the relative bias of the favored codon pair inclination among the genes, illustrated by analyzing the CABI score of the Medicago truncatula genes. CABI showed strong correlation with all other widely used measures (CAI, RCBS, SCUO) for geneexpression analysis. Surprisingly, CABI outperforms all other measures by showing better correlation with the wet-lab data. This emphasizes the importance of the neighboring codons of the favored codon in a synonymous group while estimating the expression level of a gene.

DNA array data without a corresponding statistical error measure. We propose an easy-to-implement and simple-to-use technique that uses bootstrap re-sampling to evaluate the statistical error of the nodes provided by SOM-based clustering. Comparisons between SOM and parametric clustering are presented...... for simulated as well as for two real data sets. We also implement a bootstrap-based pre-processing procedure for SOM, that improves the false discovery ratio of differentially expressedgenes. Code in Matlab is freely available, as well as some supplementary material, at the following address: https...

on global geneexpression in testicular CIS have been previously published. We have merged the two data sets on CIS samples (n = 6) and identified the shared geneexpression signature in relation to expression in normal testis. Among the top-20 highest expressedgenes, one-third was transcription factors...... development' were significantly altered and could collectively affect cellular pathways like the WNT signalling cascade, which thus may be disrupted in testicular CIS. The merged CIS data from two different microarray platforms, to our knowledge, provide the most precise CIS geneexpression signature to date....

As a case study for the Auckland Region of New Zealand, this paper investigates the potential use of gene-expression programming (GEP) in predicting specific return period events in comparison to the established and widely used Regional Flood Estimation (RFE) method. Initially calibrated to 14 gauged sites, the GEP derived model was further validated to 10 and 100 year flood events with a relative errors of 29% and 18%, respectively. This is compared to the RFE method providing 48% and 44% errors for the same flood events. While the effectiveness of GEP in predicting specific return period events is made apparent, it is argued that the derived equations should be used in conjunction with those existing methodologies rather than as a replacement.

Expression quantitative trait loci (eQTL) studies have established convincing relationships between genetic variants and geneexpression. Most of these studies focused on the mean of geneexpression level, but not the variance of geneexpression level (i.e., geneexpression variability). In the present study, we systematically explore genome-wide association between genetic variants and geneexpression variability in humans. We adapt the double generalized linear model (dglm) to simultaneously fit the means and the variances of geneexpression among the three possible genotypes of a biallelic SNP. The genomic loci showing significant association between the variances of geneexpression and the genotypes are termed expression variability QTL (evQTL). Using a data set of geneexpression in lymphoblastoid cell lines (LCLs) derived from 210 HapMap individuals, we identify cis-acting evQTL involving 218 distinct genes, among which 8 genes, ADCY1, CTNNA2, DAAM2, FERMT2, IL6, PLOD2, SNX7, and TNFRSF11B, are cross-validated using an extra expression data set of the same LCLs. We also identify ∼300 trans-acting evQTL between >13,000 common SNPs and 500 randomly selected representative genes. We employ two distinct scenarios, emphasizing single-SNP and multiple-SNP effects on expression variability, to explain the formation of evQTL. We argue that detecting evQTL may represent a novel method for effectively screening for genetic interactions, especially when the multiple-SNP influence on expression variability is implied. The implication of our results for revealing genetic mechanisms of geneexpression variability is discussed. PMID:23150607

Geneexpression is regulated by specific transcriptional circuits but also by the global expression machinery as a function of growth. Simultaneous specific and global regulation thus constitutes an additional-but often neglected-layer of complexity in geneexpression. Here, we develop an

Mammalian cells use a variety of mechanisms to control the expression of new gene transcrips elicited in response to ionizing radiation. Damage-induced proteins have been found which contain DNA binding sites located within the promoter regions of SV40 and human thymidine kinase genes. DNA binding proteins as well as proteins which bind to specific DNA lesions (e.g., XIP bp 175 binds specifically to X-ray-damaged DNA) may play a role in the initial recognition of DNA damage and may initiate DNA repair processes, along with new transcription. Mammalian geneexpression after DNA damage is also regulated via the stabilization of preexisting mRNA transcripts. Stabilized mRNA transcripts are translated into protein products not previously present in the cell due to undefined posttranscriptional modifications. Thus far, the only example of mRNA stabilization following X-irradiation is the immediate induction of tissue-type plasminogen activator. Mammalian cells synthesize new mRNA transcripts indirect response to DNA damage. Using cDNA cloning, Northern RNA blotting and nuclear run-on techniques, the levels of a variety of known and previously unknown genes dramatically increase following X-irradiation. These genes/proteins now include; a) DNA binding transcripts factors, such as the UV-responsive element binding factors, ionizing radiation-induced DNA-binding proteins, and XIP bP 175; b) proto-oncogenes, such as c-fos, c-jun, and c-myc; c) several growth-related genes, (e.g., the gadd genes, protein kinase C, IL-1, and thymidine kinase); and d) a variety of other genes, including proteases, tumor necrosis factor-alpha, and DT diaphorase. Mammalian cells respond to X-irradiation by eliciting a very complex series of events resulting in the appearance of new genes and proteins. These gene products may affect DNA repair, adaptive responses, apoptosis, SOS-type mutagenic response, and/or carcinogenesis. (J.P.N.)

promoter was only detected in 14 samples and only at a low level with no correlation to geneexpression. MSH2 geneexpression was not a prognostic factor for overall survival in univariate or multivariate analysis. The geneexpression of MSH2 is a potential quantitative marker ready for further clinical...

Geneexpression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative geneexpression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for t...

Full Text Available Integrative analysis of gene dosage, expression, and ontology (GO data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the geneexpression results. An independent cohort of 41 patients was used for validation of geneexpressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with geneexpression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1 and 13q (FAM48A, MED4 correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.

Quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) is a technique that is widely used for geneexpression analysis, and its accuracy depends on the expression stability of the internal reference genes used as normalization factors. However, many applications of qRT-PCR used housekeeping genes as internal controls without validation. In this study, the expression stability of eight candidate reference genes in three tissues (intestine, respiratory tree, and muscle) of the sea cucumber Apostichopus japonicus was assessed during normal growth and aestivation using the geNorm, NormFinder, delta CT, and RefFinder algorithms. The results indicate that the reference genes exhibited significantly different expression patterns among the three tissues during aestivation. In general, the β-tubulin (TUBB) gene was relatively stable in the intestine and respiratory tree tissues. The optimal reference gene combination for intestine was 40S ribosomal protein S18 (RPS18), TUBB, and NADH dehydrogenase (NADH); for respiratory tree, it was β-actin (ACTB), TUBB, and succinate dehydrogenase cytochrome B small subunit (SDHC); and for muscle it was α-tubulin (TUBA) and NADH dehydrogenase [ubiquinone] 1 α subcomplex subunit 13 (NDUFA13). These combinations of internal control genes should be considered for use in further studies of geneexpression in A. japonicus during aestivation.

Geneexpression is one of the main molecular processes regulating the differentiation, development, and functioning of cells and tissues. In this review a handful of relevant terms and concepts are introduced and the most common techniques used in studies of geneexpression/expression profiling (also referred to as studies of the transcriptome or…

CDX genes are classically known as regulators of axial elongation during early embryogenesis. An unsuspected role for CDX genes has been revealed during hematopoietic development. The CDX gene family member CDX2 belongs to the most frequent aberrantly expressed proto-oncogenes in human acute leukemias and is highly leukemogenic in experimental models. We used reversed transcriptase polymerase chain reaction (RT-PCR) to determine the expression level of CDX2 gene in 30 pediatric patients with acute lymphoblastic leukemia (ALL) at diagnosis and 30 healthy volunteers. ALL patients were followed up to detect minimal residual disease (MRD) on days 15 and 42 of induction. We found that CDX2 gene was expressed in 50% of patients and not expressed in controls. Associations between geneexpression and different clinical and laboratory data of patients revealed no impact on different findings. With follow up, we could not confirm that CDX2 expression had a prognostic significance.

pression of reporter gene in adult brain specific GAL4 enhancer traps of. Drosophila ... genes based on their expression pattern, thus enabling us to overcome the ... order association and storage centres of olfactory learning and memory, and ...

Full Text Available Abstract Chronic obstructive pulmonary disease (COPD is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients. Geneexpression profiling was performed on total RNA extracted from non-tumor lung tissue from 30 smokers with emphysema. Class comparison analysis based on gas transfer measurement was performed to identify differentially expressedgenes. Genes were then selected for technical validation by quantitative reverse transcriptase-PCR (qRT-PCR if also represented on microarray platforms used in previously published emphysema studies. Genes technically validated advanced to tests of biological replication by qRT-PCR using an independent test set of 62 lung samples. Class comparison identified 98 differentially expressedgenes (p p Geneexpression profiling of lung from emphysema patients identified seven candidate genes associated with emphysema severity including COL6A3, SERPINF1, ZNHIT6, NEDD4, CDKN2A, NRN1 and GSTM3.

When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this geneexpression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of geneexpression heterogeneity between classes and then scored the genes on the basis of the degree of geneexpression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

Full Text Available An important research problem in computational biology is the identification of expression programs, sets of co-expressedgenes orchestrating normal or pathological processes, and the characterization of the functional breadth of these programs. The use of human expression data compendia for discovery of such programs presents several challenges including cellular inhomogeneity within samples, genetic and environmental variation across samples, uncertainty in the numbers of programs and sample populations, and temporal behavior. We developed GeneProgram, a new unsupervised computational framework based on Hierarchical Dirichlet Processes that addresses each of the above challenges. GeneProgram uses expression data to simultaneously organize tissues into groups and genes into overlapping programs with consistent temporal behavior, to produce maps of expression programs, which are sorted by generality scores that exploit the automatically learned groupings. Using synthetic and real geneexpression data, we showed that GeneProgram outperformed several popular expression analysis methods. We applied GeneProgram to a compendium of 62 short time-series geneexpression datasets exploring the responses of human cells to infectious agents and immune-modulating molecules. GeneProgram produced a map of 104 expression programs, a substantial number of which were significantly enriched for genes involved in key signaling pathways and/or bound by NF-kappaB transcription factors in genome-wide experiments. Further, GeneProgram discovered expression programs that appear to implicate surprising signaling pathways or receptor types in the response to infection, including Wnt signaling and neurotransmitter receptors. We believe the discovered map of expression programs involved in the response to infection will be useful for guiding future biological experiments; genes from programs with low generality scores might serve as new drug targets that exhibit minimal

The selection of reference genes used for data normalization to quantify geneexpression by real-time PCR amplifications (qRT-PCR) is crucial for the accuracy of this technique. In spite of this, little information regarding such genes for qRT-PCR is available for geneexpression analyses in pathogenic fungi. Thus, we investigated the suitability of eight candidate reference genes in isolates of the human dermatophyte Trichophyton rubrum subjected to several environmental challenges, such as drug exposure, interaction with human nail and skin, and heat stress. The stability of these genes was determined by geNorm, NormFinder and Best-Keeper programs. The gene with the most stable expression in the majority of the conditions tested was rpb2 (DNA-dependent RNA polymerase II), which was validated in three T. rubrum strains. Moreover, the combination of rpb2 and chs1 (chitin synthase) genes provided for the most reliable qRT-PCR data normalization in T. rubrum under a broad range of biological conditions. To the best of our knowledge this is the first report on the selection of reference genes for qRT-PCR data normalization in dermatophytes and the results of these studies should permit further analysis of geneexpression under several experimental conditions, with improved accuracy and reliability.

Abstract Background Geneexpression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we presen...

The relationship between cell morphology, proliferation and contact inhibition was studied in normal and malignant human cells which varied in their sensitivity to contact inhibition. Their ability to proliferate was examined under conditions where the cells were constrained into different shapes. Cell proliferation was quantitated by labeling indices, which were inferred by autoradiography, and by total cell counts. The normal cells (JHU-1, IMR-90) were dependent on cell shape for proliferation capability while the transformed cells (RT4, HT1080) were shape-dependent for proliferation. Interferon (IFN) induced shape-dependent proliferation and contact inhibition in the transformed cells when used at subantiproliferative concentrations. This ability of B-IFN to confer a level of proliferation control which is characteristic of normal fibroblasts suggests a possible relationship between geneexpression mediated by IFN and those genes involved in the maintenance of regulated cell proliferation. To evaluate this possibility, cDNA libraries were constructed from IFN-treated and untreated HT1080 cells. The resulting 10 IFN-induced and 11 IFN-repressed sequences were then differentially rescreened using /sup 32/P-cDNA probes. This screening resulted in the identification of at least four cDNA sequences which appeared to be proliferation regulated as well as IFN-modulated. These cloned, regulated cDNA sequences were then used as /sup 32/P-labeled probes to study both the geneexpression at the mRNA level employing Northern blotting and slot blotting techniques.

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

Full Text Available NPR1 is an essential positive regulator of salicylic acid-induced PR geneexpression and systemic acquired resistance. Two novel full-length NPR1-like genes; MNPR1A and MNPR1B, were isolated by application of the PCR and RACE techniques. The two...

Full Text Available BACKGROUND: Real-time quantitative PCR (qPCR is still the gold-standard technique for gene-expression quantification. Recent technological advances of this method allow for the high-throughput gene-expression analysis, without the limitations of sample space and reagent used. However, non-commercial and user-friendly software for the management and analysis of these data is not available. RESULTS: The recently developed commercial microarrays allow for the drawing of standard curves of multiple assays using the same n-fold diluted samples. Data Analysis Gene (DAG Expression software has been developed to perform high-throughput gene-expression data analysis using standard curves for relative quantification and one or multiple reference genes for sample normalization. We discuss the application of DAG Expression in the analysis of data from an experiment performed with Fluidigm technology, in which 48 genes and 115 samples were measured. Furthermore, the quality of our analysis was tested and compared with other available methods. CONCLUSIONS: DAG Expression is a freely available software that permits the automated analysis and visualization of high-throughput qPCR. A detailed manual and a demo-experiment are provided within the DAG Expression software at http://www.dagexpression.com/dage.zip.

Full Text Available Abstract Background In ovo electroporation is a widely used technique to study gene function in developmental biology. Despite the widespread acceptance of this technique, no genome-wide analysis of the effects of in ovo electroporation, principally the current applied across the tissue and exogenous vector DNA introduced, on endogenous geneexpression has been undertaken. Here, the effects of electric current and expression of a GFP-containing construct, via electroporation into the midbrain of Hamburger-Hamilton stage 10 chicken embryos, are analysed by microarray. Results Both current alone and in combination with exogenous DNA expression have a small but reproducible effect on endogenous geneexpression, changing the expression of the genes represented on the array by less than 0.1% (current and less than 0.5% (current + DNA, respectively. The subset of genes regulated by electric current and exogenous DNA span a disparate set of cellular functions. However, no genes involved in the regional identity were affected. In sharp contrast to this, electroporation of a known transcription factor, Dmrt5, caused a much greater change in geneexpression. Conclusions These findings represent the first systematic genome-wide analysis of the effects of in ovo electroporation on geneexpression during embryonic development. The analysis reveals that this process has minimal impact on the genetic basis of cell fate specification. Thus, the study demonstrates the validity of the in ovo electroporation technique to study gene function and expression during development. Furthermore, the data presented here can be used as a resource to refine the set of transcriptional responders in future in ovo electroporation studies of specific gene function.

Full Text Available BACKGROUND: Numerous biochemical and physiological parameters of living organisms follow a circadian rhythm. Although such rhythmic behavior is particularly pronounced in plants, which are strictly dependent on the daily photoperiod, data on the molecular aspects of the diurnal cycle in plants is scarce and mostly concerns the model species Arabidopsis thaliana. Here we studied the leaf transcriptome in seedlings of maize, an important C4 crop only distantly related to A. thaliana, throughout a cycle of 10 h darkness and 14 h light to look for rhythmic patterns of geneexpression. RESULTS: Using DNA microarrays comprising ca. 43,000 maize-specific probes we found that ca. 12% of all genes showed clear-cut diel rhythms of expression. Cluster analysis identified 35 groups containing from four to ca. 1,000 genes, each comprising genes of similar expression patterns. Perhaps unexpectedly, the most pronounced and most common (concerning the highest number of genesexpression maxima were observed towards and during the dark phase. Using Gene Ontology classification several meaningful functional associations were found among genes showing similar diel expression patterns, including massive induction of expression of genes related to geneexpression, translation, protein modification and folding at dusk and night. Additionally, we found a clear-cut tendency among genes belonging to individual clusters to share defined transcription factor-binding sequences. CONCLUSIONS: Co-expressedgenes belonging to individual clusters are likely to be regulated by common mechanisms. The nocturnal phase of the diurnal cycle involves gross induction of fundamental biochemical processes and should be studied more thoroughly than was appreciated in most earlier physiological studies. Although some general mechanisms responsible for the diel regulation of geneexpression might be shared among plants, details of the diurnal regulation of geneexpression seem to differ

circumvented by instead matching geneexpression signatures to signatures of other experiments. FINDINGS: To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 geneexpression signatures, extracted from more than 1700...... Arabidopsis microarray experiments. CONCLUSIONS: Hereby we present a publicly available tool for robust characterization of Arabidopsis geneexpression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/....

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at ident...

To investigate the expression of the preferentially expressed antigen of melanoma (PRAME) gene in acute leukemia and its clinical significance. The level of expressed PRAME mRNA in bone marrow mononuclear cells from 34 patients with acute leukemia (AL) and in 12 bone marrow samples from healthy volunteers was measured via RT-PCR. Correlation analyses between PRAME geneexpression and the clinical characteristics (gender, age, white blood count, immunophenotype of leukemia, percentage of blast cells, and karyotype) of the patients were performed. The PRAME gene was expressed in 38.2% of all 34 patients, in 40.7% of the patients with acute myelogenous leukemia (AML, n=27), and in 28.6% of the patients with acute lymphoblastic leukemia (ALL, n=7), but was not expressed in the healthy volunteers. The difference in the expression levels between AML and ALL patients was statistically significant. The rate of geneexpression was 80% in M 3 , 33.3% in M 2 , and 28.6% in M 5 . Geneexpression was also found to be correlated with CD15 and CD33 expression and abnormal karyotype, but not with age, gender, white blood count or percentage of blast cells. The PRAME gene is highly expressed in acute leukemia and could be a useful marker to monitor minimal residual disease. This gene is also a candidate target for the immunotherapy of acute leukemia

Full Text Available Because many species-specific phenotypic differences are assumed to be caused by differential regulation of geneexpression, many recent investigations have focused on measuring transcript abundance. Despite the availability of high-throughput platforms, quantitative real-time polymerase chain reaction (RT-QPCR is often the method of choice because of its low cost and wider dynamic range. However, the accuracy of this technique heavily relies on the use of multiple valid control genes for normalization. We created a pipeline for choosing genes potentially useful as RT-QPCR control genes for measuring expression between human and chimpanzee samples across multiple tissues, using published microarrays and a measure of tissue-specificity. We identified 13 genes from the pipeline and from commonly used control genes: ACTB, USP49, ARGHGEF2, GSK3A, TBP, SDHA, EIF2B2, GPDH, YWHAZ, HPTR1, RPL13A, HMBS, and EEF2. We then tested these candidate genes and validated their expression stability across species. We established the rank order of the most preferable set of genes for single and combined tissues. Our results suggest that for at least three tissues (cerebral cortex, liver, and skeletal muscle, EIF2B2, EEF2, HMBS, and SDHA are useful genes for normalizing human and chimpanzee expression using RT-QPCR. Interestingly, other commonly used control genes, including TBP, GAPDH, and, especially ACTB do not perform as well. This pipeline could be easily adapted to other species for which expression data exist, providing taxonomically appropriate control genes for comparisons of geneexpression among species.

We used the serial analysis of geneexpression (SAGE) technique to catalogue and measure the relative levels of expression of the genesexpressed in the human peripheral retina, macula, and retinal pigment epithelium (RPE) from one or both of two humans, aged 88 and 44 years. The cone photoreceptor contribution to all transcription in the retina was found to be similar in the macula versus the retinal periphery, whereas the rod contribution was greater in the periphery versus the macula. Genes encoding structural proteins for axons were found to be expressed at higher levels in the macula versus the retinal periphery, probably reflecting the large proportion of ganglion cells in the central retina. In comparison with the younger eye, the peripheral retina of the older eye had a substantially higher proportion of mRNAs from genes encoding proteins involved in iron metabolism or protection against oxidative damage and a substantially lower proportion of mRNAs from genes encoding proteins involved in rod phototransduction. These differences may reflect the difference in age between the two donors or merely interindividual variation. The RPE library had numerous previously unencountered tags, suggesting that this cell type has a large, idiosyncratic repertoire of expressedgenes. Comparison of these libraries with 100 reported nonocular SAGE libraries revealed 89 retina-specific or enriched genesexpressed at substantial levels, of which 14 are known to cause a retinal disease and 53 are RPE-specific genes. We expect that these libraries will serve as a resource for understanding the relative expression levels of genes in the retina and the RPE and for identifying additional disease genes. PMID:11756676

TROPI (for TROPIsms) consisted of a series of experiments on the International Space Station to study the interaction between phototropism and gravitropism. As part of TROPI, we received frozen Arabidopsis seedlings from the ISS on three shuttle missions (STS-116, STS-117 and STS-120). These seedlings are being used for geneexpression studies. Unfortunately, the quality of RNA returned from the first return mission was poor while that from the second and third missions were of high quality. This indicates that some environmental parameters were not maintained during first return mission since all of these samples were stored in the same location at -80° C on the ISS. Therefore, due to the loss during the first sample return, we had to develop new protocols to maximize RNA yields and optimize labeling techniques for microarray analysis. Using these new protocols, RNA was extracted from several sets of seedlings grown in various light treatments and µg levels and microarray analyses performed. Hundreds of genes were shown to be regulated in response to microgravity and include transcription factors (WRKY, MYB, ZF families) and those involved in plant hormone signaling (auxin, ethylene, and ABA responsive genes). The characterization of the regulated pathways and genes specific to gravity and light treatments is underway. (This project is Supported By: NASA NCC2-1200).

The Agrobacterium-mediated transient assay is a relatively rapid technique and a promising approach for assessing the expression of a gene of interest. Despite the successful application of this transient expression system in several plant species, it is not well understood in spinach. In this st...

Full Text Available Large numbers of quantitative trait loci (QTL affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of geneexpression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of geneexpression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

Redox chemistry and redox regulation are central to the operation of photosynthesis and respiration. However, the roles of different oxidants and antioxidants in the regulation of photosynthetic or respiratory geneexpression remain poorly understood. Leaf transcriptome profiles of a range of Arabidopsis thaliana genotypes that are deficient in either hydrogen peroxide processing enzymes or in low molecular weight antioxidant were therefore compared to determine how different antioxidant systems that process hydrogen peroxide influence transcripts encoding proteins targeted to the chloroplasts or mitochondria. Less than 10 per cent overlap was observed in the transcriptome patterns of leaves that are deficient in either photorespiratory (catalase (cat)2) or chloroplastic (thylakoid ascorbate peroxidase (tapx)) hydrogen peroxide processing. Transcripts encoding photosystem II (PSII) repair cycle components were lower in glutathione-deficient leaves, as were the thylakoid NAD(P)H (nicotinamide adenine dinucleotide (phosphate)) dehydrogenases (NDH) mRNAs. Some thylakoid NDH mRNAs were also less abundant in tAPX-deficient and ascorbate-deficient leaves. Transcripts encoding the external and internal respiratory NDHs were increased by low glutathione and low ascorbate. Regulation of transcripts encoding specific components of the photosynthetic and respiratory electron transport chains by hydrogen peroxide, ascorbate and glutathione may serve to balance non-cyclic and cyclic electron flow pathways in relation to oxidant production and reductant availability.

Cyclins and cyclin-dependent kinase (CDK) are main regulators of the cell cycle of eukaryotes. It's assumes a significant change of their level in cells under microgravity conditions and by other physical factors actions. The clinorotation use enables to determine the influence of gravity on simulated events in the cell during the cell cycle - exit from the state of quiet stage and promotion presynthetic phase (G1) and DNA synthesis phase (S) of the cell cycle. For the clinorotation effect study on cell proliferation activity is the necessary studies of molecular mechanisms of cell cycle regulation and development of plants under altered gravity condition. The activity of cyclin D, which is responsible for the events of the cell cycle in presynthetic phase can be controlled by the action of endogenous as well as exogenous factors, but clinorotation is one of the factors that influence on genesexpression that regulate the cell cycle.These data can be used as a model for further research of cyclin - CDK complex for study of molecular mechanisms regulation of growth and proliferation. In this investigation we tried to summarize and analyze known literature and own data we obtained relatively the main regulators of the cell cycle in altered gravity condition.

Full Text Available Identifying genes that are differentially expressed in response to social interactions is informative for understanding the molecular basis of social behavior. To address this question, we described changes in geneexpression as a result of differences in the extent of social interactions. We housed threespine stickleback (Gasterosteus aculeatus females in either group conditions or individually for one week, then measured levels of geneexpression in three brain regions using RNA-sequencing. We found that numerous genes in the hindbrain/cerebellum had altered expression in response to group or individual housing. However, relatively few genes were differentially expressed in either the diencephalon or telencephalon. The list of genes upregulated in fish from social groups included many genes related to neural development and cell adhesion as well as genes with functions in sensory signaling, stress, and social and reproductive behavior. The list of genesexpressed at higher levels in individually-housed fish included several genes previously identified as regulated by social interactions in other animals. The identified genes are interesting targets for future research on the molecular mechanisms of normal social interactions.

Full Text Available The severity and prevalence of many diseases are known to differ between the sexes. Organ specific sex-biased geneexpression may underpin these and other sexually dimorphic traits. To further our understanding of sex differences in transcriptional regulation, we performed meta-analyses of sex biased geneexpression in multiple human tissues. We analysed 22 publicly available human geneexpression microarray data sets including over 2500 samples from 15 different tissues and 9 different organs. Briefly, by using an inverse-variance method we determined the effect size difference of geneexpression between males and females. We found the greatest sex differences in geneexpression in the brain, specifically in the anterior cingulate cortex, (1818 genes, followed by the heart (375 genes, kidney (224 genes, colon (218 genes and thyroid (163 genes. More interestingly, we found different parts of the brain with varying numbers and identity of sex-biased genes, indicating that specific cortical regions may influence sexually dimorphic traits. The majority of sex-biased genes in other tissues such as the bladder, liver, lungs and pancreas were on the sex chromosomes or involved in sex hormone production. On average in each tissue, 32% of autosomal genes that were expressed in a sex-biased fashion contained androgen or estrogen hormone response elements. Interestingly, across all tissues, we found approximately two-thirds of autosomal genes that were sex-biased were not under direct influence of sex hormones. To our knowledge this is the largest analysis of sex-biased geneexpression in human tissues to date. We identified many sex-biased genes that were not under the direct influence of sex chromosome genes or sex hormones. These may provide targets for future development of sex-specific treatments for diseases.

Full Text Available Abstract Background Renal cell carcinoma (RCC is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. Methods Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the geneexpression levels. Geneexpression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. Results Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressedgenes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR. Detailed comparison of geneexpression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. Conclusions This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting geneexpression patterns in RCC. Most

In the last years, tens of thousands geneexpression profiles for cells of several organisms have been monitored. Geneexpression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a geneexpression experiment is proposed for future applications of the model

The prognosis of hepatocellular carcinoma (HCC) varies following surgical resection and the large variation remains largely unexplained. Studies have revealed the ability of clinicopathologic parameters and geneexpression to predict HCC prognosis. However, there has been little systematic effort to compare the performance of these two types of predictors or combine them in a comprehensive model. Tumor and adjacent non-tumor liver tissues were collected from 272 ethnic Chinese HCC patients who received curative surgery. We combined clinicopathologic parameters and geneexpression data (from both tissue types) in predicting HCC prognosis. Cross-validation and independent studies were employed to assess prediction. HCC prognosis was significantly associated with six clinicopathologic parameters, which can partition the patients into good- and poor-prognosis groups. Within each group, geneexpression data further divide patients into distinct prognostic subgroups. Our predictive genes significantly overlap with previously published gene sets predictive of prognosis. Moreover, the predictive genes were enriched for genes that underwent normal-to-tumor gene network transformation. Previously documented liver eSNPs underlying the HCC predictive gene signatures were enriched for SNPs that associated with HCC prognosis, providing support that these genes are involved in key processes of tumorigenesis. When applied individually, clinicopathologic parameters and geneexpression offered similar predictive power for HCC prognosis. In contrast, a combination of the two types of data dramatically improved the power to predict HCC prognosis. Our results also provided a framework for understanding the impact of geneexpression on the processes of tumorigenesis and clinical outcome

Full Text Available The use of RT-qPCR provides a powerful tool for geneexpression studies; however, the proper interpretation of the obtained data is crucially dependent on accurate normalization based on stable reference genes. Recently, strong evidence has been shown indicating that the expression of many commonly used reference genes may vary significantly due to diverse experimental conditions. The isolation of pancreatic islets is a complicated procedure which creates severe mechanical and metabolic stress leading possibly to cellular damage and alteration of geneexpression. Despite of this, freshly isolated islets frequently serve as a control in various geneexpression and intervention studies. The aim of our study was to determine expression of 16 candidate reference genes and one gene of interest (F3 in isolated rat pancreatic islets during short-term cultivation in order to find a suitable endogenous control for geneexpression studies. We compared the expression stability of the most commonly used reference genes and evaluated the reliability of relative and absolute quantification using RT-qPCR during 0-120 hrs after isolation. In freshly isolated islets, the expression of all tested genes was markedly depressed and it increased several times throughout the first 48 hrs of cultivation. We observed significant variability among samples at 0 and 24 hrs but substantial stabilization from 48 hrs onwards. During the first 48 hrs, relative quantification failed to reflect the real changes in respective mRNA concentrations while in the interval 48-120 hrs, the relative expression generally paralleled the results determined by absolute quantification. Thus, our data call into question the suitability of relative quantification for geneexpression analysis in pancreatic islets during the first 48 hrs of cultivation, as the results may be significantly affected by unstable expression of reference genes. However, this method could provide reliable information

Throughout the last decade many laboratories have shown that mRNA levels in formalin-fixed and paraffin-embedded (FPE) tissue specimens can be quantified by reverse transcriptase-polymerase chain reaction (RT-PCR) techniques despite the extensive RNA fragmentation that occurs in tissues so preserved. We have developed RT-PCR methods that are sensitive, precise, and that have multianalyte capability for potential wide use in clinical research and diagnostic assays. Here it is shown that the extent of fragmentation of extracted FPE tissue RNA significantly increases with archive storage time. Probe and primer sets for RT-PCR assays based on amplicons that are both short and homogeneous in length enable effective reference gene-based data normalization for cross comparison of specimens that differ substantially in age. A 48-gene assay used to compare geneexpression profiles from the same breast cancer tissue that had been either frozen or FPE showed very similar profiles after reference gene-based normalization. A 92-gene assay, using RNA extracted from three 10-μm FPE sections of archival breast cancer specimens (dating from 1985 to 2001) yielded analyzable data for these genes in all 62 tested specimens. The results were substantially concordant when estrogen receptor, progesterone receptor, and HER2 receptor status determined by RT-PCR was compared with immunohistochemistry assays for these receptors. Furthermore, the results highlight the advantages of RT-PCR over immunohistochemistry with respect to quantitation and dynamic range. These findings support the development of RT-PCR analysis of FPE tissue RNA as a platform for multianalyte clinical diagnostic tests. PMID:14695316

Full Text Available Abstract Background Geneexpression studies require appropriate normalization methods. One such method uses stably expressed reference genes. Since suitable reference genes appear to be unique for each tissue, we have identified an optimal set of the most stably expressedgenes in human blood that can be used for normalization. Methods Whole-genome Affymetrix Human 2.0 Plus arrays were examined from 526 samples of males and females ages 2 to 78, including control subjects and patients with Tourette syndrome, stroke, migraine, muscular dystrophy, and autism. The top 100 most stably expressedgenes with a broad range of expression levels were identified. To validate the best candidate genes, we performed quantitative RT-PCR on a subset of 10 genes (TRAP1, DECR1, FPGS, FARP1, MAPRE2, PEX16, GINS2, CRY2, CSNK1G2 and A4GALT, 4 commonly employed reference genes (GAPDH, ACTB, B2M and HMBS and PPIB, previously reported to be stably expressed in blood. Expression stability and ranking analysis were performed using GeNorm and NormFinder algorithms. Results Reference genes were ranked based on their expression stability and the minimum number of genes needed for nomalization as calculated using GeNorm showed that the fewest, most stably expressedgenes needed for acurate normalization in RNA expression studies of human whole blood is a combination of TRAP1, FPGS, DECR1 and PPIB. We confirmed the ranking of the best candidate control genes by using an alternative algorithm (NormFinder. Conclusion The reference genes identified in this study are stably expressed in whole blood of humans of both genders with multiple disease conditions and ages 2 to 78. Importantly, they also have different functions within cells and thus should be expressed independently of each other. These genes should be useful as normalization genes for microarray and RT-PCR whole blood studies of human physiology, metabolism and disease.

The capability to measure geneexpression on board spacecrafts opens the doors to a large number of experiments on the influence of space environment on biological systems that will profoundly impact our ability to conduct safe and effective space travel, and might also shed light on terrestrial physiology or biological function and human disease and aging processes. Measurements of geneexpression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, determine metabolic basis of microbial pathogenicity and drug resistance, test our ability to sustain and grow in space organisms that can be used for life support and in situ resource utilization during long-duration space exploration, and monitor both the spacecraft environment and crew health. These and other applications hold significant potential for discoveries in space biology, biotechnology and medicine. Accordingly, supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measuring microbial expression of thousands of genes from multiple samples. The instrument will be capable of (1) lysing bacterial cell walls, (2) extracting and purifying RNA released from cells, (3) hybridizing it on a microarray and (4) providing electrochemical readout, all in a microfluidics cartridge. The prototype under development is suitable for deployment on nanosatellite platforms developed by the NASA Small Spacecraft Office. The first target application is to cultivate and measure geneexpression of the photosynthetic bacterium Synechococcus elongatus, i.e. a cyanobacterium known to exhibit remarkable metabolic diversity and resilience to adverse conditions

Full Text Available High-throughput mutagenesis of the mammalian genome is a powerful means to facilitate analysis of gene function. Gene trapping in embryonic stem cells (ESCs is the most widely used form of insertional mutagenesis in mammals. However, the rules governing its efficiency are not fully understood, and the effects of vector design on the likelihood of gene-trapping events have not been tested on a genome-wide scale.In this study, we used public gene-trap data to model gene-trap likelihood. Using the association of gene length and geneexpression with gene-trap likelihood, we constructed spline-based regression models that characterize which genes are susceptible and which genes are resistant to gene-trapping techniques. We report results for three classes of gene-trap vectors, showing that both length and expression are significant determinants of trap likelihood for all vectors. Using our models, we also quantitatively identified hotspots of gene-trap activity, which represent loci where the high likelihood of vector insertion is controlled by factors other than length and expression. These formalized statistical models describe a high proportion of the variance in the likelihood of a gene being trapped by expression-dependent vectors and a lower, but still significant, proportion of the variance for vectors that are predicted to be independent of endogenous geneexpression.The findings of significant expression and length effects reported here further the understanding of the determinants of vector insertion. Results from this analysis can be applied to help identify other important determinants of this important biological phenomenon and could assist planning of large-scale mutagenesis efforts.

The conversion of the cellular prion protein (PrP C ) to the protease-resistant isoform is the key event in chronic neurodegenerative diseases, including transmissible spongiform encephalopathies (TSEs). Increased iron in prion-related disease has been observed due to the prion protein-ferritin complex. Additionally, the accumulation and conversion of recombinant PrP (rPrP) is specifically derived from Fe(III) but not Fe(II). Fe(III)-mediated PK-resistant PrP (PrP res ) conversion occurs within a complex cellular environment rather than via direct contact between rPrP and Fe(III). In this study, differentially expressedgenes correlated with prion degeneration by Fe(III) were identified using Affymetrix microarrays. Following Fe(III) treatment, 97 genes were differentially expressed, including 85 upregulated genes and 12 downregulated genes (≥1.5-fold change in expression). However, Fe(II) treatment produced moderate alterations in geneexpression without inducing dramatic alterations in geneexpression profiles. Moreover, functional grouping of identified genes indicated that the differentially regulated genes were highly associated with cell growth, cell maintenance, and intra- and extracellular transport. These findings showed that Fe(III) may influence the expression of genes involved in PrP folding by redox mechanisms. The identification of genes with altered expression patterns in neural cells may provide insights into PrP conversion mechanisms during the development and progression of prion-related diseases. - Highlights: • Differential genes correlated with prion degeneration by Fe(III) were identified. • Genes were identified in cell proliferation and intra- and extracellular transport. • In PrP degeneration, redox related genes were suggested. • Cbr2, Rsad2, Slc40a1, Amph and Mvd were expressed significantly.

Full Text Available This article contains data related to the research articles "Spatial and Temporal Analysis of GeneExpression during Growth and Fusion of the Mouse Facial Prominences" (Feng et al., 2009 [1] and “Systems Biology of facial development: contributions of ectoderm and mesenchyme” (Hooper et al., 2017 In press [2]. Embryonic mammalian craniofacial development is a complex process involving the growth, morphogenesis, and fusion of distinct facial prominences into a functional whole. Aberrant gene regulation during this process can lead to severe craniofacial birth defects, including orofacial clefting. As a means to understand the genes involved in facial development, we had previously dissected the embryonic mouse face into distinct prominences: the mandibular, maxillary or nasal between E10.5 and E12.5. The prominences were then processed intact, or separated into ectoderm and mesenchyme layers, prior analysis of RNA expression using microarrays (Feng et al., 2009, Hooper et al., 2017 in press [1,2]. Here, individual geneexpression profiles have been built from these datasets that illustrate the timing of geneexpression in whole prominences or in the separated tissue layers. The data profiles are presented as an indexed and clickable list of the genes each linked to a graphical image of that gene׳sexpression profile in the ectoderm, mesenchyme, or intact prominence. These data files will enable investigators to obtain a rapid assessment of the relative expression level of any gene on the array with respect to time, tissue, prominence, and expression trajectory.

Full Text Available Stably ExpressedGenes (SEGs whose expression varies within a narrow range may be involved in core cellular processes necessary for basic functions. To identify such genes, we re-analyzed existing RNA-Seq geneexpression profiles across 11 organs at 4 developmental stages (from immature to old age in both sexes of F344 rats (n = 4/group; 320 samples. Expression changes (calculated as the maximum expression / minimum expression for each gene of >19000 genes across organs, ages, and sexes ranged from 2.35 to >109-fold, with a median of 165-fold. The expression of 278 SEGs was found to vary ≤4-fold and these genes were significantly involved in protein catabolism (proteasome and ubiquitination, RNA transport, protein processing, and the spliceosome. Such stability of expression was further validated in human samples where the expression variability of the homologous human SEGs was significantly lower than that of other genes in the human genome. It was also found that the homologous human SEGs were generally less subject to non-synonymous mutation than other genes, as would be expected of stably expressedgenes. We also found that knockout of SEG homologs in mouse models was more likely to cause complete preweaning lethality than non-SEG homologs, corroborating the fundamental roles played by SEGs in biological development. Such stably expressedgenes and pathways across life-stages suggest that tight control of these processes is important in basic cellular functions and that perturbation by endogenous (e.g., genetics or exogenous agents (e.g., drugs, environmental factors may cause serious adverse effects.

Objective: To investigate the molecular etiology of breast cancer by way of studying the differential expression and initial function of the related genes in the occurrence and development of breast cancer. Methods: Two hundred and eighty-eight human tumor related genes were chosen for preparation of the oligochips probe. mRNA was extracted from 16 breast cancer tissues and the corresponding normal breast tissues, and cDNA probe was prepared through reverse-transcription and hybridized with the gene chip. A laser focused fluorescent scanner was used to scan the chip. The different geneexpressions were thereafter automatically compared and analyzed between the two sample groups. Cy3/Cy5＞3.5 meant significant up-regulation. Cy3/Cy5＜0.25 meant significant down-regulation. Results: The comparison between the breast cancer tissues and their corresponding normal tissues showed that 84 genes had differential expression in the Chip. Among the differently expressedgenes, there were 4 genes with significant down-regulation and 6 with significant up-regulation. Compared with normal breast tissues, differentially expressedgenes did partially exist in the breast cancer tissues. Conclusion: Changes in multi-geneexpression regulations take place during the occurrence and development of breast cancer; and the research on related genes can help understanding the mechanism of tumor occurrence.

Epigenetics provides an important layer of information on top of the DNA sequence and is essential for establishing geneexpression profiles. Extensive studies have shown that nuclear DNA methylation and histone modifications influence nuclear geneexpression. However, it remains unclear whether

Conclusion: The expression of KLK2 gene in people with prostate cancer is the higher than the healthy person; finally, according to the results, it could be mentioned that the KLK2 gene considered as a useful factor in prostate cancer, whose expression is associated with progression and development of the prostate cancer.

The relationship between the structure of genes and their expression is a relatively new aspect of genome organization and regulation. With more genome sequences and expression data becoming available, bioinformatics approaches can help the further elucidation of the relationships between gene

Jan 31, 2011 ... A decrease in mRNA levels for cytochrome c oxidase (COX) subunits was observed in skeletal muscle of hypothyroid rats. However, the precise expression mechanisms of the related genes in hypothyroid state still remain unclear. This study investigated geneexpressions of DNA methyltransferases.

pool former. We have molecularly cloned and characterized the rat ACBP gene family which comprises one expressed and four processed pseudogenes. One of these was shown to exist in two allelic forms. A comprehensive computer-aided analysis of the promoter region of the expressed ACBP gene revealed...

In order to identify differentially expressedgenes involved in heat shock response, cDNA amplified fragment length polymorphism (cDNA-AFLP) and quantitative real-time polymerase chain reaction (QPCR) were used to study geneexpression of eggplant seedlings subjected to 0, 6 and 12 h at 43°C. A total of 53 of over ...

Much information can be obtained from knowledge of the relative expression level of each gene in the transcriptome. With the current advances in technology as little as a single cell is required as starting material for geneexpression experiments. The mRNA from a single cell may be linearly...

A decrease in mRNA levels for cytochrome c oxidase (COX) subunits was observed in skeletal muscle of hypothyroid rats. However, the precise expression mechanisms of the related genes in hypothyroid state still remain unclear. This study investigated geneexpressions of DNA methyltransferases (Dnmts), DNA ...

Microarray analysis of the geneexpression profile in triethylene glycol dimethacrylate-treated human dental pulp cells. ... Conclusions: Our results suggest that TEGDMA can change the many functions of hDPCs through large changes in geneexpression levels and complex interactions with different signaling pathways.

Arbuscular mycorrhizas (AMs) are a unique example of symbiosis between two eukaryotes, soil fungi and plants. This association induces important physiological changes in each partner that lead to reciprocal benefits, mainly in nutrient supply. The symbiosis results from modifications in plant and fungal cell organization caused by specific changes in geneexpression. Recently, much effort has gone into studying these geneexpression patterns to identify a wider spectrum of genes involved. We aim in this review to describe AM symbiosis in terms of current knowledge on plant and fungal geneexpression profiles.

Full Text Available AIM: To discuss the expression and clinical significance of Pax6 gene in retinoblastoma(Rb. METHODS: Totally 15 cases of fresh Rb organizations were selected as observation group and 15 normal retinal organizations as control group. Western-Blot and reverse transcriptase polymerase chain reaction(RT-PCRmethods were used to detect Pax6 protein and Pax6 mRNA expressions of the normal retina organizations and Rb organizations. At the same time, Western Blot method was used to detect the Pax6 gene downstream MATH5 and BRN3b differentiation gene protein level expression. After the comparison between two groups, the expression and clinical significance of Pax6 gene in Rb were discussed. RESULTS: In the observation group, average value of mRNA expression of Pax6 gene was 0.99±0.03; average value of Pax6 gene protein expression was 2.07±0.15; average value of BRN3b protein expression was 0.195±0.016; average value of MATH5 protein expression was 0.190±0.031. They were significantly higher than the control group, and the differences were statistically significant(PCONCLUSION: Abnormal expression of Pax6 gene is likely to accelerate the occurrence of Rb.

Cerebral ischemia is one of the strongest stimuli for gene induction in the brain. Hundreds of genes have been found to be induced by brain ischemia. Many genes are involved in neurodestructive functions such as excitotoxicity, inflammatory response and neuronal apoptosis. However, cerebral ischemia is also a powerful reformatting and reprogramming stimulus for the brain through neuroprotective geneexpression. Several genes may participate in both cellular responses. Thus, isolation of candidate genes for neuroprotection strategies and interpretation of expression changes have been proven difficult. Nevertheless, many studies are being carried out to improve the knowledge of the gene activation and protein expression following ischemic stroke, as well as in the development of new therapies that modify biochemical, molecular and genetic changes underlying cerebral ischemia. Owing to the complexity of the process involving numerous critical genesexpressed differentially in time, space and concentration, ongoing therapeutic efforts should be based on multiple interventions at different levels. By modification of the acute geneexpression induced by ischemia or the apoptotic gene program, gene therapy is a promising treatment but is still in a very experimental phase. Some hurdles will have to be overcome before these therapies can be introduced into human clinical stroke trials. Copyright 2006 S. Karger AG, Basel.

Full Text Available Abstract Background The annotation of many genomes is limited, with a large proportion of identified genes lacking functional assignments. The construction of gene co-expression networks is a powerful approach that presents a way of integrating information from diverse geneexpression datasets into a unified analysis which allows inferences to be drawn about the role of previously uncharacterised genes. Using this approach, we generated a condition-free gene co-expression network for the chicken using data from 1,043 publically available Affymetrix GeneChip Chicken Genome Arrays. This data was generated from a diverse range of experiments, including different tissues and experimental conditions. Our aim was to identify gene co-expression modules and generate a tool to facilitate exploration of the functional chicken genome. Results Fifteen modules, containing between 24 and 473 genes, were identified in the condition-free network. Most of the modules showed strong functional enrichment for particular Gene Ontology categories. However, a few showed no enrichment. Transcription factor binding site enrichment was also noted. Conclusions We have demonstrated that this chicken gene co-expression network is a useful tool in gene function prediction and the identification of putative novel transcription factors and binding sites. This work highlights the relevance of this methodology for functional prediction in poorly annotated genomes such as the chicken.

The FANTOM consortium has generated a large geneexpression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between geneexpression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing geneexpression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between geneexpression patterns than previously anticipated.

The FANTOM consortium has generated a large geneexpression dataset of different cell lines and tissue cultures using the single-molecule sequencing technology of HeliscopeCAGE. This provides a unique opportunity to investigate novel associations between geneexpression over time and different cell types. Here, we create a MatLab wrapper for a powerful and computationally intensive set of statistics known as Maximal Information Coefficient, and then calculate this statistic for a large, comprehensive dataset containing geneexpression of a variety of differentiating tissues. We then distinguish between linear and nonlinear associations, and then create gene association networks. Following this analysis, we are then able to identify clusters of linear gene associations that then associate nonlinearly with other clusters of linearity, providing insight to much more complex connections between geneexpression patterns than previously anticipated.

Several studies point to the placenta as the primary cause of pre-eclampsia. Our objective was to identify placental genes that may contribute to the development of pre-eclampsia. RNA was purified from tissue biopsies from eleven pre-eclamptic placentas and eighteen normal controls. Messenger RNA...... expression from pooled samples was analysed by microarrays. Verification of the expression of selected genes was performed using real-time PCR. A surprisingly low number of genes (21 out of 15,000) were identified as differentially expressed. Among these were genes not previously associated with pre-eclampsia...... as bradykinin B1 receptor and a 14-3-3 protein, but also genes that have already been connected with pre-eclampsia, for example, inhibin beta A subunit and leptin. A low number of genes were repeatedly identified as differentially expressed, because they may represent the endpoint of a cascade of events...

May 2, 2008 ... responsible in negative feedback loop reaction of central oscillator in plant circadian clock system. The level of geneexpression was found to be high four hours after dawn in flowering shoots and flower. This paper reported the isolation and characterization of the gene. Key words: LHY gene, circadian ...

levels of neutral genetic divergence, a high number of genes were significantly differentially expressed between North Sea and Baltic Sea flounders maintained in a long-term reciprocal transplantation experiment mimicking natural salinities. Several of the differentially regulated genes could be directly...... linked to fitness traits. These findings demonstrate that flounders, despite little neutral genetic divergence between populations, are differently adapted to local environmental conditions and imply that adaptation in geneexpression could be common in other marine organisms with similar low levels...

Nervous systems consist of diverse populations of neurons that are anatomically and functionally distinct. The diversity of neurons and the precision with which they are interconnected suggest that specific genes or sets of genes are activated in some neurons but not expressed in others. Experimentally, this problem may be considered at two levels. First, what is the total number of genesexpressed in the brain, and how are they distributed among the different populations of neurons? Second, ...

Full Text Available Abstract Background Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. Results We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for geneexpression data, and then perform a comprehensive analysis of 3581 Affymetrix® geneexpression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Conclusions Despite the widespread use of GO and KEGG gene sets in bacterial geneexpression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial geneexpression data may improve statistical power and utility of expression data.

Three studies of geneexpression during the division cycle of Schizosaccharomyces pombe led to the proposal that a large number of genes are expressed at particular times during the S. pombe cell cycle. Yet only a small fraction of genes proposed to be expressed in a cell-cycle-dependent manner are reproducible in all three published studies. In addition to reproducibility problems, questions about expression amplitudes, cell-cycle timing of expression, synchronization artifacts, and the problem with methods for synchronizing cells must be considered. These problems and complications prompt the idea that caution should be used before accepting the conclusion that there are a large number of genesexpressed in a cell-cycle-dependent manner in S. pombe.

Goosegrass (Eleusine indica) is one of the most serious annual grassy weeds worldwide, and its evolved herbicide-resistant populations are more difficult to control. Quantitative real-time PCR (qPCR) is a common technique for investigating the resistance mechanism; however, there is as yet no report on the systematic selection of stable reference genes for goosegrass. This study proposed to test the expression stability of 9 candidate reference genes in goosegrass in different tissues and developmental stages and under stress from three types of herbicide. The results show that for different developmental stages and organs (control), eukaryotic initiation factor 4 A (eIF-4) is the most stable reference gene. Chloroplast acetolactate synthase (ALS) is the most stable reference gene under glyphosate stress. Under glufosinate stress, eIF-4 is the best reference gene. Ubiquitin-conjugating enzyme (UCE) is the most stable reference gene under quizalofop-p-ethyl stress. The gene eIF-4 is the recommended reference gene for goosegrass under the stress of all three herbicides. Moreover, pairwise analysis showed that seven reference genes were sufficient to normalize the geneexpression data under three herbicides treatment. This study provides a list of reliable reference genes for transcript normalization in goosegrass, which will facilitate resistance mechanism studies in this weed species.

The existence of genes shared by mammalian sex chromosomes has been predicted on both evolutionary and functional grounds. However, the only experimental evidence for such genes in humans is the cell-surface antigen encoded by loci on the X and Y chromosomes (MIC2X and MIC2Y, respectively), which is recognized by the monoclonal antibody 12E7. Using the bacteriophage λgt11 expression system in Escherichia coli and immunoscreening techniques, the authors have isolated a cDNA clone whose primary product is recognized by 12E7. Southern blot analysis using somatic cell hybrids containing only the human X or Y chromosomes shows that the sequences reacting with the cDNA clone are localized to the sex chromosomes. In addition, the clone hybridizes to DNAs isolated from mouse cells that have been transfected with human DNA and selected for 12E7 expression on the fluorescence-activated cell sorter. The authors conclude that the cDNA clone encodes the 12E7 antigen, which is the primary product of the MIC2 loci. The clone was used to explore sequence homology between MIC2X and MIC2Y; these loci are closely related, if not identical

Full Text Available We used digital long serial analysis of geneexpression to discover geneexpression differences between node-negative and node-positive colorectal tumors and developed a multigene classifier able to discriminate between these two tumor types. We prepared and sequenced long serial analysis of geneexpression libraries from one node-negative and one node-positive colorectal tumor, sequenced to a depth of 26,060 unique tags, and identified 262 tags significantly differentially expressed between these two tumors (P < 2 x 10-6. We confirmed the tag-to-gene assignments and differential expression of 31 genes by quantitative real-time polymerase chain reaction, 12 of which were elevated in the node-positive tumor. We analyzed the expression levels of these 12 upregulated genes in a validation panel of 23 additional tumors and developed an optimized seven-gene logistic regression classifier. The classifier discriminated between node-negative and node-positive tumors with 86% sensitivity and 80% specificity. Receiver operating characteristic analysis of the classifier revealed an area under the curve of 0.86. Experimental manipulation of the function of one classification gene, Fibronectin, caused profound effects on invasion and migration of colorectal cancer cells in vitro. These results suggest that the development of node-positive colorectal cancer occurs in part through elevated epithelial FN1 expression and suggest novel strategies for the diagnosis and treatment of advanced disease.

NUP98-HOXD13 (NHD13) and CALM-AF10 (CA10) are oncogenic fusion proteins produced by recurrent chromosomal translocations in patients with acute myeloid leukemia (AML). Transgenic mice that express these fusions develop AML with a long latency and incomplete penetrance, suggesting that collaborating genetic events are required for leukemic transformation. We employed genetic techniques to identify both preleukemic abnormalities in healthy transgenic mice as well as collaborating events leading to leukemic transformation. Candidate gene resequencing revealed that 6 of 27 (22%) CA10 AMLs spontaneously acquired a Ras pathway mutation and 8 of 27 (30%) acquired an Flt3 mutation. Two CA10 AMLs acquired an Flt3 internal-tandem duplication, demonstrating that these mutations can be acquired in murine as well as human AML. Geneexpression profiles revealed a marked upregulation of Hox genes, particularly Hoxa5, Hoxa9, and Hoxa10 in both NHD13 and CA10 mice. Furthermore, mir196b, which is embedded within the Hoxa locus, was overexpressed in both CA10 and NHD13 samples. In contrast, the Hox cofactors Meis1 and Pbx3 were differentially expressed; Meis1 was increased in CA10 AMLs but not NHD13 AMLs, whereas Pbx3 was consistently increased in NHD13 but not CA10 AMLs. Silencing of Pbx3 in NHD13 cells led to decreased proliferation, increased apoptosis, and decreased colony formation in vitro, suggesting a previously unexpected role for Pbx3 in leukemic transformation. Published by Elsevier Inc.

The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR geneexpression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate geneexpression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting geneexpression studies.

Migration and proliferation of vascular smooth muscle cells (SMCs) are key events in atherosclerosis. However, little is known about alterations in geneexpression upon transition of the quiescent, contractile SMC to the proliferative SMC. We performed serial analysis of geneexpression (SAGE) of

Full Text Available We present a PCR-based laboratory exercise that can be used with first- or second-year biology students to help overcome common misconceptions about geneexpression. Biology students typically do not have a clear understanding of the difference between genes (DNA and geneexpression (mRNA/protein and often believe that genes exist in an organism or cell only when they are expressed. This laboratory exercise allows students to carry out a PCR-based experiment designed to challenge their misunderstanding of the difference between genes and geneexpression. Students first transform E. coli with an inducible GFP gene containing plasmid and observe induced and un-induced colonies. The following exercise creates cognitive dissonance when actual PCR results contradict their initial (incorrect predictions of the presence of the GFP gene in transformed cells. Field testing of this laboratory exercise resulted in learning gains on both knowledge and application questions on concepts related to genes and geneexpression.

Full Text Available Abstract Background The availability of microarrays measuring thousands of genes simultaneously across hundreds of biological conditions represents an opportunity to understand both individual biological pathways and the integrated workings of the cell. However, translating this amount of data into biological insight remains a daunting task. An important initial step in the analysis of microarray data is clustering of genes with similar behavior. A number of classical techniques are commonly used to perform this task, particularly hierarchical and K-means clustering, and many novel approaches have been suggested recently. While these approaches are useful, they are not without drawbacks; these methods can find clusters in purely random data, and even clusters enriched for biological functions can be skewed towards a small number of processes (e.g. ribosomes. Results We developed Nearest Neighbor Networks (NNN, a graph-based algorithm to generate clusters of genes with similar expression profiles. This method produces clusters based on overlapping cliques within an interaction network generated from mutual nearest neighborhoods. This focus on nearest neighbors rather than on absolute distance measures allows us to capture clusters with high connectivity even when they are spatially separated, and requiring mutual nearest neighbors allows genes with no sufficiently similar partners to remain unclustered. We compared the clusters generated by NNN with those generated by eight other clustering methods. NNN was particularly successful at generating functionally coherent clusters with high precision, and these clusters generally represented a much broader selection of biological processes than those recovered by other methods. Conclusion The Nearest Neighbor Networks algorithm is a valuable clustering method that effectively groups genes that are likely to be functionally related. It is particularly attractive due to its simplicity, its success in the

Maternal genes present in mature oocytes play a crucial role in the early development of silkworm. Although maternal genes have been widely studied in many other species, there has been limited research in Bombyx mori. High-throughput next generation sequencing provides a practical method for gene discovery on a genome-wide level. Herein, a transcriptome study was used to identify maternal-related genes from silkworm eggs. Unfertilized eggs from five different stages of early development were used to detect the changing situation of geneexpression. The expressedgenes showed different patterns over time. Seventy-six maternal genes were annotated according to homology analysis with Drosophila melanogaster. More than half of the differentially expressed maternal genes fell into four expression patterns, while the expression patterns showed a downward trend over time. The functional annotation of these material genes was mainly related to transcription factor activity, growth factor activity, nucleic acid binding, RNA binding, ATP binding, and ion binding. Additionally, twenty-two gene clusters including maternal genes were identified from 18 scaffolds. Altogether, we plotted a profile for the maternal genes of Bombyx mori using a digital geneexpression profiling method. This will provide the basis for maternal-specific signature research and improve the understanding of the early development of silkworm. PMID:29462160

Full Text Available Abstract Background A common observation in the analysis of geneexpression data is that many genes display similarity in their expression patterns and therefore appear to be co-regulated. However, the variation associated with microarray data and the complexity of the experimental designs make the acquisition of co-expressedgenes a challenge. We developed a novel method for Extracting microarray geneexpression Patterns and Identifying co-expressedGenes, designated as EPIG. The approach utilizes the underlying structure of geneexpression data to extract patterns and identify co-expressedgenes that are responsive to experimental conditions. Results Through evaluation of the correlations among profiles, the magnitude of variation in geneexpression profiles, and profile signal-to-noise ratio's, EPIG extracts a set of patterns representing co-expressedgenes. The method is shown to work well with a simulated data set and microarray data obtained from time-series studies of dauer recovery and L1 starvation in C. elegans and after ultraviolet (UV or ionizing radiation (IR-induced DNA damage in diploid human fibroblasts. With the simulated data set, EPIG extracted the appropriate number of patterns which were more stable and homogeneous than the set of patterns that were determined using the CLICK or CAST clustering algorithms. However, CLICK performed better than EPIG and CAST with respect to the average correlation between clusters/patterns of the simulated data. With real biological data, EPIG extracted more dauer-specific patterns than CLICK. Furthermore, analysis of the IR/UV data revealed 18 unique patterns and 2661 genes out of approximately 17,000 that were identified as significantly expressed and categorized to the patterns by EPIG. The time-dependent patterns displayed similar and dissimilar responses between IR and UV treatments. Gene Ontology analysis applied to each pattern-related subset of co-expressedgenes revealed underlying

Full Text Available Abstract Background Geneexpression in lipopolysaccharide (LPS-stimulated monocytes is mainly studied by quantitative real-time reverse transcription PCR (RT-qPCR using GAPDH (glyceraldehyde 3-phosphate dehydrogenase or ACTB (beta-actin as reference gene for normalization. Expression of traditional reference genes has been shown to vary substantially under certain conditions leading to invalid results. To investigate whether traditional reference genes are stably expressed in LPS-stimulated monocytes or if RT-qPCR results are dependent on the choice of reference genes, we have assessed and evaluated geneexpression stability of twelve candidate reference genes in this model system. Results Twelve candidate reference genes were quantified by RT-qPCR in LPS-stimulated, human monocytes and evaluated using the programs geNorm, Normfinder and BestKeeper. geNorm ranked PPIB (cyclophilin B, B2M (beta-2-microglobulin and PPIA (cyclophilin A as the best combination for geneexpression normalization in LPS-stimulated monocytes. Normfinder suggested TBP (TATA-box binding protein and B2M as the best combination. Compared to these combinations, normalization using GAPDH alone resulted in significantly higher changes of TNF-α (tumor necrosis factor-alpha and IL10 (interleukin 10 expression. Moreover, a significant difference in TNF-α expression between monocytes stimulated with equimolar concentrations of LPS from N. meningitides and E. coli, respectively, was identified when using the suggested combinations of reference genes for normalization, but stayed unrecognized when employing a single reference gene, ACTB or GAPDH. Conclusions Geneexpression levels in LPS-stimulated monocytes based on RT-qPCR results differ significantly when normalized to a single gene or a combination of stably expressed reference genes. Proper evaluation of reference gene stabiliy is therefore mandatory before reporting RT-qPCR results in LPS-stimulated monocytes.

BACKGROUND: The mechanism of sex determination in zebrafish is largely unknown and neither sex chromosomes nor a sex-determining gene have been identified. This indicates that sex determination in zebrafish is mediated by genetic signals from autosomal genes. The aim of this study was to determine...... the precise timing of expression of six genes previously suggested to be associated with sex differentiation in zebrafish. The current study investigates the expression of all six genes in the same individual fish with extensive sampling dates during sex determination and -differentiation. RESULTS......: In the present study, we have used quantitative real-time PCR to investigate the expression of ar, sox9a, dmrt1, fig alpha, cyp19a1a and cyp19a1b during the expected sex determination and gonadal sex differentiation period. The expression of the genes expected to be high in males (ar, sox9a and dmrt1a) and high...

In cells, the bistable kinetics of geneexpression can be observed on the level of (i) one gene with positive feedback between protein and mRNA production, (ii) two genes with negative mutual feedback between protein and mRNA production, or (iii) in more complex cases. We analyse the interplay of two genes of type (ii) governed by a gene of type (i) during cellular growth. In particular, using kinetic Monte Carlo simulations, we show that in the case where gene 1, operating in the bistable regime, regulates mutually inhibiting genes 2 and 3, also operating in the bistable regime, the latter genes may eventually be trapped either to the state with high transcriptional activity of gene 2 and low activity of gene 3 or to the state with high transcriptional activity of gene 3 and low activity of gene 2. The probability to get to one of these states depends on the values of the model parameters. If genes 2 and 3 are kinetically equivalent, the probability is equal to 0.5. Thus, our model illustrates how different intracellular states can be chosen at random with predetermined probabilities. This type of kinetics of geneexpression may be behind complex processes occurring in cells, e.g., behind the choice of the fate by stem cells

We have developed and implemented a serial experiment in molecular cloning laboratory course for undergraduate students majored in biotechnology. "Pseudomonas putida xylE" gene, encoding catechol 2, 3-dioxygenase, was manipulated to learn molecular biology techniques. The integration of cloning, expression, and enzyme assay gave students…

Full Text Available The postgenomic era of large-scale geneexpression studies is inundating drug abuse researchers and many other scientists with findings related to geneexpression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in geneexpression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in geneexpression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of geneexpression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

Full Text Available Abstract Background Marfan syndrome (MFS is a heritable connective tissue disorder caused by mutations in the fibrillin-1 gene. This syndrome constitutes a significant identifiable subtype of aortic aneurysmal disease, accounting for over 5% of ascending and thoracic aortic aneurysms. Results We used spotted membrane DNA macroarrays to identify genes whose altered expression levels may contribute to the phenotype of the disease. Our analysis of 4132 genes identified a subset with significant expression differences between skin fibroblast cultures from unaffected controls versus cultures from affected individuals with known fibrillin-1 mutations. Subsequently, 10 genes were chosen for validation by quantitative RT-PCR. Conclusion Differential expression of many of the validated genes was associated with MFS samples when an additional group of unaffected and MFS affected subjects were analyzed (p-value -6 under the null hypothesis that expression levels in cultured fibroblasts are unaffected by MFS status. An unexpected observation was the range of individual geneexpression. In unaffected control subjects, expression ranges exceeding 10 fold were seen in many of the genes selected for qRT-PCR validation. The variation in expression in the MFS affected subjects was even greater.

Full Text Available Gene therapy has generated worldwide attention as a new medical technology. While non-viral gene vectors are promising candidates as gene carriers, they have several issues such as toxicity and low transfection efficiency. We have hypothesized that the generation of reactive oxygen species (ROS affects geneexpression in polyplex supported gene delivery systems. The effect of ROS on the geneexpression of polyplex was evaluated using a nitroxide radical-containing nanoparticle (RNP as an ROS scavenger. When polyethyleneimine (PEI/pGL3 or PEI alone was added to the HeLa cells, ROS levels increased significantly. In contrast, when (PEI/pGL3 or PEI was added with RNP, the ROS levels were suppressed. The luciferase expression was increased by the treatment with RNP in a dose-dependent manner and the cellular uptake of pDNA was also increased. Inflammatory cytokines play an important role in ROS generation in vivo. In particular, tumor necrosis factor (TNF-α caused intracellular ROS generation in HeLa cells and decreased geneexpression. RNP treatment suppressed ROS production even in the presence of TNF-α and increased geneexpression. This anti-inflammatory property of RNP suggests that it may be used as an effective adjuvant for non-viral gene delivery systems.

Geneexpression profiles of clinical cohorts can be used to identify genes that are correlated with a clinical variable of interest such as patient outcome or response to a particular drug. However, expression measurements are susceptible to technical bias caused by variation in extraneous factors...... such as RNA quality and array hybridization conditions. If such technical bias is correlated with the clinical variable of interest, the likelihood of identifying false positive genes is increased. Here we describe a method to visualize an expression matrix as a projection of all genes onto a plane defined...... by a clinical variable and a technical nuisance variable. The resulting plot indicates the extent to which each gene is correlated with the clinical variable or the technical variable. We demonstrate this method by applying it to three clinical trial microarray data sets, one of which identified genes that may...

Geneexpression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes ("housekeeping genes") are essential to verify geneexpression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity) which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1) which demonstrated no altered geneexpression levels in all tested conditions and therefore represent good candidates for the standardization of geneexpression studies in altered gravity.

Comparing the overlap between sets of differentially expressedgenes (DEGs) within or between transcriptome studies is regularly used to infer similarities between biological processes. Significant overlap between two sets of DEGs is usually determined by a simple test. The number of potentially overlapping genes is compared to the number of genes that actually occur in both lists, treating every gene as equal. However, geneexpression is controlled by transcription factors that bind to a variable number of transcription factor binding sites, leading to variation among genes in general variability of their expression. Neglecting this variability could therefore lead to inflated estimates of significant overlap between DEG lists. With computer simulations, we demonstrate that such biases arise from variation in the control of geneexpression. Significant overlap commonly arises between two lists of DEGs that are randomly generated, assuming that the control of geneexpression is variable among genes but consistent between corresponding experiments. More overlap is observed when transcription factors are specific to their binding sites and when the number of genes is considerably higher than the number of different transcription factors. In contrast, overlap between two DEG lists is always lower than expected when the genetic architecture of expression is independent between the two experiments. Thus, the current methods for determining significant overlap between DEGs are potentially confounding biologically meaningful overlap with overlap that arises due to variability in control of expression among genes, and more sophisticated approaches are needed.

To study the pathogenic importance of the rheumatoid factor (RF) in rheumatoid arthritis (RA) and to identify genes differentially expressed in patients and healthy individuals, total RNA was isolated from peripheral blood mononuclear cells (PBMC) from eight RF-positive and six RF-negative RA...... patients, and seven healthy controls. Geneexpression of about 10,000 genes were examined using oligonucleotide-based DNA chip microarrays. The analyses showed no significant differences in PBMC expression patterns from RF-positive and RF-negative patients. However, comparisons of geneexpression patterns...

Full Text Available Scleroderma is a clinically heterogeneous disease with a complex phenotype. The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production.We analyzed the genome-wide patterns of geneexpression with DNA microarrays in skin biopsies from distinct scleroderma subsets including 17 patients with systemic sclerosis (SSc with diffuse scleroderma (dSSc, 7 patients with SSc with limited scleroderma (lSSc, 3 patients with morphea, and 6 healthy controls. 61 skin biopsies were analyzed in a total of 75 microarray hybridizations. Analysis by hierarchical clustering demonstrates nearly identical patterns of geneexpression in 17 out of 22 of the forearm and back skin pairs of SSc patients. Using this property of the geneexpression, we selected a set of 'intrinsic' genes and analyzed the inherent data-driven groupings. Distinct patterns of geneexpression separate patients with dSSc from those with lSSc and both are easily distinguished from normal controls. Our data show three distinct patient groups among the patients with dSSc and two groups among patients with lSSc. Each group can be distinguished by unique geneexpression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program. The intrinsic groups are statistically significant (p<0.001 and each has been mapped to clinical covariates of modified Rodnan skin score, interstitial lung disease, gastrointestinal involvement, digital ulcers, Raynaud's phenomenon and disease duration. We report a 177-gene signature that is associated with severity of skin disease in dSSc.Genome-wide geneexpression profiling of skin biopsies demonstrates that the heterogeneity in scleroderma can be measured quantitatively with DNA microarrays. The diversity in geneexpression demonstrates multiple distinct geneexpression programs in the skin of patients with scleroderma.

Microarray technology continues to gain increased acceptance in the drug development process, particularly at the stage of toxicology and safety assessment. In the current study, microarrays were used to investigate geneexpression changes associated with hepatotoxicity, the most commonly reported clinical liability with pharmaceutical agents. Acetaminophen, methotrexate, methapyrilene, furan and phenytoin were used as benchmark compounds capable of inducing specific but different types of hepatotoxicity. The goal of the work was to define geneexpression profiles capable of distinguishing the different subtypes of hepatotoxicity. Sprague-Dawley rats were orally dosed with acetaminophen (single dose, 4500 mg/kg for 6, 24 and 72 h), methotrexate (1 mg/kg per day for 1, 7 and 14 days), methapyrilene (100 mg/kg per day for 3 and 7 days), furan (40 mg/kg per day for 1, 3, 7 and 14 days) or phenytoin (300 mg/kg per day for 14 days). Hepatic geneexpression was assessed using toxicology-specific gene arrays containing 684 target genes or expressed sequence tags (ESTs). Principal component analysis (PCA) of geneexpression data was able to provide a clear distinction of each compound, suggesting that geneexpression data can be used to discern different hepatotoxic agents and toxicity endpoints. Geneexpression data were applied to the multiplicity-adjusted permutation test and significantly changed genes were categorized and correlated to hepatotoxic endpoints. Repression of enzymes involved in lipid oxidation (acyl-CoA dehydrogenase, medium chain, enoyl CoA hydratase, very long-chain acyl-CoA synthetase) were associated with microvesicular lipidosis. Likewise, subsets of genes associated with hepatotocellular necrosis, inflammation, hepatitis, bile duct hyperplasia and fibrosis have been identified. The current study illustrates that expression profiling can be used to: (1) distinguish different hepatotoxic endpoints; (2) predict the development of toxic endpoints; and

Full Text Available BACKGROUND: Lactogenesis includes two stages. Stage I begins a few weeks before parturition. Stage II is initiated around the time of parturition and extends for several days afterwards. METHODOLOGY/PRINCIPAL FINDINGS: To better understand the molecular events underlying these changes, genome-wide geneexpression profiling was conducted using digital geneexpression (DGE on bovine mammary tissue at three time points (on approximately day 35 before parturition (-35 d, day 7 before parturition (-7 d and day 3 after parturition (+3 d. Approximately 6.2 million (M, 5.8 million (M and 6.1 million (M 21-nt cDNA tags were sequenced in the three cDNA libraries (-35 d, -7 d and +3 d, respectively. After aligning to the reference sequences, the three cDNA libraries included 8,662, 8,363 and 8,359 genes, respectively. With a fold change cutoff criteria of ≥ 2 or ≤-2 and a false discovery rate (FDR of ≤ 0.001, a total of 812 genes were significantly differentially expressed at -7 d compared with -35 d (stage I. Gene ontology analysis showed that those significantly differentially expressedgenes were mainly associated with cell cycle, lipid metabolism, immune response and biological adhesion. A total of 1,189 genes were significantly differentially expressed at +3 d compared with -7 d (stage II, and these genes were mainly associated with the immune response and cell cycle. Moreover, there were 1,672 genes significantly differentially expressed at +3 d compared with -35 d. Gene ontology analysis showed that the main differentially expressedgenes were those associated with metabolic processes. CONCLUSIONS: The results suggest that the mammary gland begins to lactate not only by a gain of function but also by a broad suppression of function to effectively push most of the cell's resources towards lactation.

Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of geneexpression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of geneexpression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in geneexpression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311

Geneexpression is a key intermediate level that genotypes lead to a particular trait. Geneexpression is affected by various factors including genotypes of genetic variants. With an aim of delineating the genetic impact on geneexpression, we build a deep auto-encoder model to assess how good genetic variants will contribute to geneexpression changes. This new deep learning model is a regression-based predictive model based on the MultiLayer Perceptron and Stacked Denoising Auto-encoder (MLP-SAE). The model is trained using a stacked denoising auto-encoder for feature selection and a multilayer perceptron framework for backpropagation. We further improve the model by introducing dropout to prevent overfitting and improve performance. To demonstrate the usage of this model, we apply MLP-SAE to a real genomic datasets with genotypes and geneexpression profiles measured in yeast. Our results show that the MLP-SAE model with dropout outperforms other models including Lasso, Random Forests and the MLP-SAE model without dropout. Using the MLP-SAE model with dropout, we show that geneexpression quantifications predicted by the model solely based on genotypes, align well with true geneexpression patterns. We provide a deep auto-encoder model for predicting geneexpression from SNP genotypes. This study demonstrates that deep learning is appropriate for tackling another genomic problem, i.e., building predictive models to understand genotypes' contribution to geneexpression. With the emerging availability of richer genomic data, we anticipate that deep learning models play a bigger role in modeling and interpreting genomics.

More than two decades of intense research have allowed gene therapy to move from the laboratory to the clinical setting, where its use for the treatment of human pathologies has been considerably increased in the last years. However, many crucial questions remain to be solved in this challenging field. In vivo imaging with positron emission tomography (PET) by combination of the appropriate PET reporter gene and PET reporter probe could provide invaluable qualitative and quantitative information to answer multiple unsolved questions about gene therapy. PET imaging could be used to define parameters not available by other techniques that are of substantial interest not only for the proper understanding of the gene therapy process, but also for its future development and clinical application in humans. This review focuses on the molecular biology basis of gene therapy and molecular imaging, describing the fundamentals of in vivo geneexpression imaging by PET, and the application of PET to gene therapy, as a technology that can be used in many different ways. It could be applied to avoid invasive procedures for gene therapy monitoring; accurately diagnose the pathology for better planning of the most adequate therapeutic approach; as treatment evaluation to image the functional effects of gene therapy at the biochemical level; as a quantitative noninvasive way to monitor the location, magnitude and persistence of geneexpression over time; and would also help to a better understanding of vector biology and pharmacology devoted to the development of safer and more efficient vectors.

Objective: To explore radioresistance correlative genes in IRM-2 inbred mouse. Methods: The total RNA was extracted from spleen cells of IRM-2 and their parent 615 and ICR/JCL mouse. The mRNA differential display technique was used to analyze geneexpression differences. Each differential bands were amplified by PCR, cloned and sequenced. Results: There were 75 differential expression bands appearing in IRM-2 mouse but not in 615 and ICR/JCL mouse. Fifty-two pieces of cDNA sequences were got by sequencing. Twenty-one expressed sequence tags (EST) that were not the same as known mice genes were found and registered by comparing with GenBank database. Conclusion: Twenty-one EST denote that radioresistance correlative genes may be in IRM-2 mouse, which have laid a foundation for isolating and identifying radioresistance correlative genes in further study. (authors)

The ideal reference, or control, gene for the study of geneexpression in a given organism should be expressed at a medium‑high level for easy detection, should be expressed at a constant/stable level throughout different cell types and within the same cell type undergoing different treatments, and should maintain these features through as many different tissues of the organism. From a biological point of view, these theoretical requirements of an ideal reference gene appear to be best suited to housekeeping (HK) genes. Recent advancements in the quality and completeness of human expression microarray data and in their statistical analysis may provide new clues toward the quantitative standardization of human geneexpression studies in biology and medicine, both cross‑ and within‑tissue. The systematic approach used by the present study is based on the Transcriptome Mapper tool and exploits the automated reassignment of probes to corresponding genes, intra‑ and inter‑sample normalization, elaboration and representation of geneexpression values in linear form within an indexed and searchable database with a graphical interface recording quantitative levels of expression, expression variability and cross‑tissue width of expression for more than 31,000 transcripts. The present study conducted a meta‑analysis of a pool of 646 expression profile data sets from 54 different human tissues and identified actin γ 1 as the HK gene that best fits the combination of all the traditional criteria to be used as a reference gene for general use; two ribosomal protein genes, RPS18 and RPS27, and one aquaporin gene, POM121 transmembrane nucleporin C, were also identified. The present study provided a list of tissue‑ and organ‑specific genes that may be most suited for the following individual tissues/organs: Adipose tissue, bone marrow, brain, heart, kidney, liver, lung, ovary, skeletal muscle and testis; and also provides in these cases a representative

Full Text Available Abstract Background The use of geneexpression in venous blood either as a pharmacodynamic marker in clinical trials of drugs or as a diagnostic test requires knowledge of the variability in expression over time in healthy volunteers. Here we defined a normal range of geneexpression over 6 months in the blood of four cohorts of healthy men and women who were stratified by age (22–55 years and > 55 years and gender. Methods Eleven immunomodulatory genes likely to play important roles in inflammatory conditions such as rheumatoid arthritis and infection in addition to four genes typically used as reference genes were examined by quantitative reverse transcription-polymerase chain reaction (qRT-PCR, as well as the full genome as represented by Affymetrix HG U133 Plus 2.0 microarrays. Results Geneexpression levels as assessed by qRT-PCR and microarray were relatively stable over time with ~2% of genes as measured by microarray showing intra-subject differences over time periods longer than one month. Fifteen genes varied by gender. The eleven genes examined by qRT-PCR remained within a limited dynamic range for all individuals. Specifically, for the seven most stably expressedgenes (CXCL1, HMOX1, IL1RN, IL1B, IL6R, PTGS2, and TNF, 95% of all samples profiled fell within 1.5–2.5 Ct, the equivalent of a 4- to 6-fold dynamic range. Two subjects who experienced severe adverse events of cancer and anemia, had microarray geneexpression profiles that were distinct from normal while subjects who experienced an infection had only slightly elevated levels of inflammatory markers. Conclusion This study defines the range and variability of geneexpression in healthy men and women over a six-month period. These parameters can be used to estimate the number of subjects needed to observe significant differences from normal geneexpression in clinical studies. A set of genes that varied by gender was also identified as were a set of genes with elevated

. Nine clusters of genes with significant differential expression over time and 49 functional charts were found in the analysed testis samples. Prominent pathways in the prepubertal testis were associated with tissue renewal, cell respiration and increased endocytocis. E-cadherines may be associated...... with the onset of pubertal development. With elevated steroidogenesis (weeks 16 to 27), there was an increase in the expression of genes in the MAPK pathway, STAR and its analogue STARD6. A pubertal shift in genes coding for cellular cholesterol transport was observed. Increased expression of meiotic pathways...

Full length mRNA sequences of Ac-β-actin and Ac-gapdh, and partial mRNA sequences of Ac-18SrRNA and Ac-ubiquitin were cloned from pineapple in this study. The four genes were tested as housekeeping genes in three experimental sets. GeNorm and NormFinder analysis revealed that β-actin was the most ...

of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with geneexpression and other functional attributes, (iv) identifying putative complexes and functional modules......Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context...... and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape....

This review summarizes the current understanding of the role of nuclear bodies in regulating geneexpression. The compartmentalization of cellular processes, such as ribosome biogenesis, RNA processing, cellular response to stress, transcription, modification and assembly of spliceosomal snRNPs, histone gene synthesis and nuclear RNA retention, has significant implications for gene regulation. These functional nuclear domains include the nucleolus, nuclear speckle, nuclear stress body, transcription factory, Cajal body, Gemini of Cajal body, histone locus body and paraspeckle. We herein review the roles of nuclear bodies in regulating geneexpression and their relation to human health and disease. PMID:24040563

.... With the advent of new bioimaging technology and the advancement of efficient gene targeting strategies, they found an opportunity to apply these state-of-the-art molecular tools to their problem...

HNTEP cells were grown in basal medium and treated with DHT in different conditions. HNTEP cells under treatment with DHT (10-13 M) induced an increase in FHL-2 expression. In turn, high DHT concentrations (10-8 M) induced an increase in the expression SHP-1. The present data suggest that the SHP-1 and FHL-2 ...

PRC2 genes were analyzed for their number of gene duplications, d N /d S ratios and expression patterns among Brassicaceae and Gramineae species. Although both amino acid sequences and copy number of the PRC2 genes were generally well conserved in both Brassicaceae and Gramineae species, we observed that some rapidly evolving genes experienced duplications and expression pattern changes. After multiple duplication events, all but one or two of the duplicated copies tend to be silenced. Silenced copies were reactivated in the endosperm and showed ectopic expression in developing seeds. The results indicated that rapid evolution of some PRC2 genes is initially caused by a relaxation of selective constraint following the gene duplication events. Several loci could become maternally expressed imprinted genes and acquired functional roles in the endosperm.

Whenever geneexpression is being examined, it is essential that a normalization process is carried out to eliminate non-biological variations. The use of reference genes, such as glyceraldehyde-3-phosphate dehydrogenase, actin, and ribosomal protein genes, is the usual method of choice for normalizing geneexpression. Although reference genes are used to normalize target geneexpression, a major problem is that the stability of these genes differs among tissues, developmental stages, species, and responses to abiotic factors. Therefore, the use and validation of multiple reference genes are required. This review discusses the reasons that why RT-qPCR has become the preferred method for validating results of geneexpression profiles, the use of specific and non-specific dyes and the importance of use of primers and probes for qPCR as well as to discuss several statistical algorithms developed to help the validation of potential reference genes. The conflicts arising in the use of classical reference genes in gene normalization and their replacement with novel references are also discussed by citing the high stability and low stability of classical and novel reference genes under various biotic and abiotic experimental conditions by employing various methods applied for the reference genes amplification.

Full Text Available Abstract Background Geneexpression patterns of olfactory receptors (ORs are an important component of the signal encoding mechanism in the olfactory system since they determine the interactions between odorant ligands and sensory neurons. We have developed the Olfactory Receptor Microarray Database (ORMD to house OR geneexpression data. ORMD is integrated with the Olfactory Receptor Database (ORDB, which is a key repository of OR gene information. Both databases aim to aid experimental research related to olfaction. Description ORMD is a Web-accessible database that provides a secure data repository for OR microarray experiments. It contains both publicly available and private data; accessing the latter requires authenticated login. The ORMD is designed to allow users to not only deposit geneexpression data but also manage their projects/experiments. For example, contributors can choose whether to make their datasets public. For each experiment, users can download the raw data files and view and export the geneexpression data. For each OR gene being probed in a microarray experiment, a hyperlink to that gene in ORDB provides access to genomic and proteomic information related to the corresponding olfactory receptor. Individual ORs archived in ORDB are also linked to ORMD, allowing users access to the related microarray geneexpression data. Conclusion ORMD serves as a data repository and project management system. It facilitates the study of microarray experiments of geneexpression in the olfactory system. In conjunction with ORDB, ORMD integrates geneexpression data with the genomic and functional data of ORs, and is thus a useful resource for both olfactory researchers and the public.

The capability to measure geneexpression on board spacecraft opens the door to a large number of high-value experiments on the influence of the space environment on biological systems. For example, measurements of geneexpression will help us to understand adaptation of terrestrial life to conditions beyond the planet of origin, identify deleterious effects of the space environment on a wide range of organisms from microbes to humans, develop effective countermeasures against these effects, and determine the metabolic bases of microbial pathogenicity and drug resistance. These and other applications hold significant potential for discoveries in space biology, biotechnology, and medicine. Supported by funding from the NASA Astrobiology Science and Technology Instrument Development Program, we are developing a fully automated, miniaturized, integrated fluidic system for small spacecraft capable of in-situ measurement of expression of several hundreds of microbial genes from multiple samples. The instrument will be capable of (1) lysing cell walls of bacteria sampled from cultures grown in space, (2) extracting and purifying RNA released from cells, (3) hybridizing the RNA on a microarray and (4) providing readout of the microarray signal, all in a single microfluidics cartridge. The device is suitable for deployment on nanosatellite platforms developed by NASA Ames' Small Spacecraft Division. To meet space and other technical constraints imposed by these platforms, a number of technical innovations are being implemented. The integration and end-to-end technological and biological validation of the instrument are carried out using as a model the photosynthetic bacterium Synechococcus elongatus, known for its remarkable metabolic diversity and resilience to adverse conditions. Each step in the measurement process-lysis, nucleic acid extraction, purification, and hybridization to an array-is assessed through comparison of the results obtained using the instrument with

Full Text Available Cancers of the pancreas originate from both the endocrine and exocrine elements of the organ, and represent a major cause of cancer-related death. This study provides a comprehensive assessment of geneexpression for pancreatic tumors, the normal pancreas, and nonneoplastic pancreatic disease.DNA microarrays were used to assess the geneexpression for surgically derived pancreatic adenocarcinomas, islet cell tumors, and mesenchymal tumors. The addition of normal pancreata, isolated islets, isolated pancreatic ducts, and pancreatic adenocarcinoma cell lines enhanced subsequent analysis by increasing the diversity in geneexpression profiles obtained. Exocrine, endocrine, and mesenchymal tumors displayed unique geneexpression profiles. Similarities in geneexpression support the pancreatic duct as the origin of adenocarcinomas. In addition, genes highly expressed in other cancers and associated with specific signal transduction pathways were also found in pancreatic tumors.The scope of the present work was enhanced by the inclusion of publicly available datasets that encompass a wide spectrum of human tissues and enabled the identification of candidate genes that may serve diagnostic and therapeutic goals.

Full Text Available Abstract Background The biological phenotype of a cell, such as a characteristic visual image or behavior, reflects activities derived from the expression of collections of genes. As such, an ability to measure the expression of these genes provides an opportunity to develop more precise and varied sets of phenotypes. However, to use this approach requires computational methods that are difficult to implement and apply, and thus there is a critical need for intelligent software tools that can reduce the technical burden of the analysis. Tools for geneexpression analyses are unusually difficult to implement in a user-friendly way because their application requires a combination of biological data curation, statistical computational methods, and database expertise. Results We have developed SIGNATURE, a web-based resource that simplifies geneexpression signature analysis by providing software, data, and protocols to perform the analysis successfully. This resource uses Bayesian methods for processing geneexpression data coupled with a curated database of geneexpression signatures, all carried out within a GenePattern web interface for easy use and access. Conclusions SIGNATURE is available for public use at http://genepattern.genome.duke.edu/signature/.

Full Text Available Abstract Background Changes in gene regulation are thought to be crucial for the adaptation of organisms to their environment. Transcriptome analyses can be used to identify candidate genes for ecological adaptation, but can be complicated by variation in geneexpression between tissues, sexes, or individuals. Here we use high-throughput RNA sequencing of a single Drosophila melanogaster tissue to detect brain-specific differences in geneexpression between the sexes and between two populations, one from the ancestral species range in sub-Saharan Africa and one from the recently colonized species range in Europe. Results Relatively few genes (Cyp6g1 and CHKov1. Conclusions Analysis of the brain transcriptome revealed many genes differing in expression between populations that were not detected in previous studies using whole flies. There was little evidence for sex-specific regulatory adaptation in the brain, as most expression differences between populations were observed in both males and females. The enrichment of genes with sexually dimorphic expression on the X chromosome is consistent with dosage compensation mechanisms affecting sex-biased expression in somatic tissues.

TNF-α regulates immune cells and acts as an endogenous pyrogen. Reverse transcription polymerase chain reaction (RT-PCR) is one of the most commonly used methods for geneexpression analysis. Among the alternatives to PCR, loop-mediated isothermal amplification (LAMP) shows good potential in terms of specificity and sensitivity. However, few studies have compared RT-PCR and LAMP for human geneexpression analysis. Therefore, in the present study, we compared one-step RT-PCR, two-step RT-LAMP and one-step RT-LAMP for human geneexpression analysis. We compared three geneexpression analysis methods using the human TNF-α gene as a biomarker from peripheral blood cells. Total RNA from the three selected febrile patients were subjected to the three different methods of geneexpression analysis. In the comparison of three geneexpression analysis methods, the detection limit of both one-step RT-PCR and one-step RT-LAMP were the same, while that of two-step RT-LAMP was inferior. One-step RT-LAMP takes less time, and the experimental result is easy to determine. One-step RT-LAMP is a potentially useful and complementary tool that is fast and reasonably sensitive. In addition, one-step RT-LAMP could be useful in environments lacking specialized equipment or expertise.

We analyzed changes in geneexpression during male meiosis in Petunia by combining the meiotic staging of pollen mother cells from a single anther with cDNA-AFLP transcript profiling of mRNA from the synchronously developing sister anthers. The transcript profiling experiments focused on the identification of genes with a modulated expression profile during meiosis, while premeiotic archesporial cells and postmeiotic microspores served as a reference. About 8000 transcript tags, estimated at 30% of the total transcriptome, were generated, of which around 6% exhibited a modulated geneexpression pattern at meiosis. Cluster analysis revealed a transcriptional cascade that coincides with the initiation and progression through all stages of the two meiotic divisions. Fragments that exhibited high expression specifically during meiosis I were characterized further by sequencing; 90 out of the 293 sequenced fragments showed homology with known genes, belonging to a wide range of gene classes, including previously characterized meiotic genes. In-situ hybridization experiments were performed to determine the spatial expression pattern for five selected transcript tags. Its concurrence with cDNA-AFLP transcript profiles indicates that this is an excellent approach to study genes involved in specialized processes such as meiosis. Our data set provides the potential to unravel unique meiotic genes that are as yet elusive to reverse genetics approaches.

Full Text Available The huge amount of geneexpression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the geneexpression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of geneexpression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select geneexpression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the geneexpression signatures.

Rabbits of the Alicia strain, derived from rabbits expressing the VHa2 allotype, have a mutation in the H chain locus that has a cis effect upon the expression of VHa2 and VHa- genes. A small deletion at the most J-proximal (3') end of the VH locus leads to low expression of all the genes on the entire chromosome in heterozygous ali mutants and altered relative expression of VH genes in homozygotes. To study VH geneexpression and regulation, we used the polymerase chain reaction to amplify the VH genesexpressed in spleens of young and adult wild-type and mutant Alicia rabbits. The cDNA from reverse transcription of splenic mRNA was amplified and polymerase chain reaction libraries were constructed and screened with oligonucleotides from framework regions 1 and 3, as well as JH. Thirty-three VH-positive clones were sequenced and analyzed. We found that in mutant Alicia rabbits, products of the first functional VH gene (VH4a2), (or VH4a2-like genes) were expressed in 2- to 8-wk-olds. Expression of both the VHx and VHy types of VHa- genes was also elevated but the relative proportions of VHx and VHy, especially VHx, decreased whereas the relative levels of expression of VH4a2 or VH4a2-like genes increased with age. Our results suggest that the appearance of sequences resembling that of the VH1a2, which is deleted in the mutant ali rabbits, could be caused by alterations of the sequences of the rearranged VH4a2 genes by gene conversions and/or rearrangement of upstream VH1a2-like genes later in development.

Vitellogenin (Vtg) and estrogen receptor (ER) geneexpression levels were measured in largemouth bass to evaluate the activation of the ER-mediated pathway by estradiol (E2). Single injections of E2 ranging from 0.0005 to 5 mg/kg up-regulated plasma Vtg in a dose-dependent manner. Vtg and ER mRNAs were measured using partial cDNA sequences corresponding to the C-terminal domain for Vtg and the ligand-binding domain of ER?? sequences. After acute E2-exposures (2 mg/kg), Vtg and ER mRNAs and plasma Vtg levels peaked after 2 days. The rate of ER mRNA accumulation peaked 36-42 h earlier than Vtg mRNA. The expression window for ER defines the primary response to E2 in largemouth bass and that for Vtg a delayed primary response. The specific effect of E2 on other estrogen-regulated genes was tested during these same time windows using differential display RT-PCR. Specific up-regulated genes that are expressed in the same time window as Vtg were ERp72 (a membrane-bound disulfide isomerase) and a gene with homology to an expressedgene identified in zebrafish. Genes that were expressed in a pattern that mimics the ER include the gene for zona radiata protein ZP2, and a gene with homology to an expressedgene found in winter flounder. One gene for fibrinogen ?? was down-regulated and an unidentified gene was transiently up-regulated after 12 h of exposure and returned to basal levels by 48 h. Taken together these studies indicate that the acute molecular response to E2 involves a complex network of responses over time. ?? 2002 Elsevier Science Ireland Ltd. All rights reserved.

The current study aimed to investigate the coding sequence, polymorphisms, and expression of the RERG gene in indigenous Chinese goats. cDNA of RERG, obtained through reverse transcription PCR was analyzed using bioinformatic techniques. Polymorphisms in the exon regions of the RERG gene were identified and their associations with growth traits in three varieties of indigenous Chinese goats were investigated. Expression of the RERG gene in three goat breeds of the same age was detected using real-time quantitative PCR. The results revealed that the cDNA of RERG, which contained a complete open reading frame of 20-620 bp, was 629 bp in length. The associated accession numbers in GenBank are JN672576, JQ917222, and JN580309 for the QianBei Ma goat, the GuiZhou white goat, and the GuiZhou black goat, respectively. Four consistent SNP sites were found in the exon regions of the RERG gene for the three goat breeds. mRNA expression of the RERG gene differed between different tissues in adult goats of same age. The highest expression was observed in lung and spleen tissues, while the lowest expression was recorded in thymus gland tissue. In addition, the expression of the RERG gene in the muscle of Guizhou white goat, GuiZhou black goat, and QianBei Ma goat decreased sequentially. Our results lay the foundations for further investigation into the role of the RERG gene in goat growth traits.

at identifying PfEMP1 features associated with high virulence. Here we present the first effective method for sequence analysis of var genesexpressed in field samples: a sequential PCR and next generation sequencing based technique applied on expressed var sequence tags and subsequently on long range PCR......, encoded by ~60 highly variable 'var' genes per haploid genome. PfEMP1 is exported to the surface of infected erythrocytes and is thought to be fundamental to immune evasion by adhesion to host and parasite factors. The highly variable nature has constituted a roadblock in var expression studies aimed...

BACKGROUND The understanding of the mechanisms regulating human oocyte maturation is still rudimentary. We have identified transcripts differentially expressed between immature and mature oocytes, and cumulus cells. METHODS Using oligonucleotides microarrays, genome wide geneexpression was studied in pooled immature and mature oocytes or cumulus cells from patients who underwent IVF. RESULTS In addition to known genes such as DAZL, BMP15 or GDF9, oocytes upregulated 1514 genes. We show that PTTG3 and AURKC are respectively the securin and the Aurora kinase preferentially expressed during oocyte meiosis. Strikingly, oocytes overexpressed previously unreported growth factors such as TNFSF13/APRIL, FGF9, FGF14, and IL4, and transcription factors including OTX2, SOX15 and SOX30. Conversely, cumulus cells, in addition to known genes such as LHCGR or BMPR2, overexpressed cell-tocell signaling genes including TNFSF11/RANKL, numerous complement components, semaphorins (SEMA3A, SEMA6A, SEMA6D) and CD genes such as CD200. We also identified 52 genes progressively increasing during oocyte maturation, comprising CDC25A and SOCS7. CONCLUSION The identification of genes up and down regulated during oocyte maturation greatly improves our understanding of oocyte biology and will provide new markers that signal viable and competent oocytes. Furthermore, genes found expressed in cumulus cells are potential markers of granulosa cell tumors. PMID:16571642

Full Text Available Abstract Background DNA microarrays are a powerful tool for monitoring the expression of tens of thousands of genes simultaneously. With the advance of microarray technology, the challenge issue becomes how to analyze a large amount of microarray data and make biological sense of them. Affymetrix GeneChips are widely used microarrays, where a variety of statistical algorithms have been explored and used for detecting significant genes in the experiment. These methods rely solely on the quantitative data, i.e., signal intensity; however, qualitative data are also important parameters in detecting differentially expressedgenes. Results AffyMiner is a tool developed for detecting differentially expressedgenes in Affymetrix GeneChip microarray data and for associating gene annotation and gene ontology information with the genes detected. AffyMiner consists of the functional modules, GeneFinder for detecting significant genes in a treatment versus control experiment and GOTree for mapping genes of interest onto the Gene Ontology (GO space; and interfaces to run Cluster, a program for clustering analysis, and GenMAPP, a program for pathway analysis. AffyMiner has been used for analyzing the GeneChip data and the results were presented in several publications. Conclusion AffyMiner fills an important gap in finding differentially expressedgenes in Affymetrix GeneChip microarray data. AffyMiner effectively deals with multiple replicates in the experiment and takes into account both quantitative and qualitative data in identifying significant genes. AffyMiner reduces the time and effort needed to compare data from multiple arrays and to interpret the possible biological implications associated with significant changes in a gene's expression.

Abstract Geneexpression levels change as an individual ages and responds to environmental conditions. With the exception of humans, such patterns have principally been studied under controlled conditions, overlooking the array of developmental and environmental influences that organisms encounter under conditions in which natural selection operates. We used high-throughput RNA sequencing (RNA-Seq) of whole blood to assess the relative impacts of social status, age, disease, and sex on geneexpression levels in a natural population of gray wolves (Canis lupus). Our findings suggest that age is broadly associated with geneexpression levels, whereas other examined factors have minimal effects on geneexpression patterns. Further, our results reveal evolutionarily conserved signatures of senescence, such as immunosenescence and metabolic aging, between wolves and humans despite major differences in life history and environment. The effects of aging on geneexpression levels in wolves exhibit conservation with humans, but the more rapid expression differences observed in aging wolves is evolutionarily appropriate given the species’ high level of extrinsic mortality due to intraspecific aggression. Some expression changes that occur with age can facilitate physical age-related changes that may enhance fitness in older wolves. However, the expression of these ancestral patterns of aging in descendant modern dogs living in highly modified domestic environments may be maladaptive and cause disease. This work provides evolutionary insight into aging patterns observed in domestic dogs and demonstrates the applicability of studying natural populations to investigate the mechanisms of aging. PMID:27189566

Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray geneexpression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass geneexpression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray geneexpression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass geneexpression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

Six biotin-containing proteins are present in plants, representing at least four different biotin enzymes. The physiological function of these biotin enzymes is not understood. Streptavidin, a protein from Streptomyces avidinii, binds tightly and specifically to biotin causing inactivation of biotin enzymes. One approach to elucidating the physiological function of biotin enzymes in plant metabolism is to create transgenic plants expressing the streptavidin gene. A plasmid containing a fused streptavidin-beta-galactosidase gene has been expressed in E. coli. We also have constructed various fusion genes that include an altered CaMV 35S promoter, signal peptides to target the streptavidin protein to specific organelles, and the streptavidin coding gene. We are examining the expression of these genes in cells of carrot

and chromosomes, owing to differences in selective pressures: transcriptome change was slow in nervous tissues and rapid in testes, slower in rodents than in apes and monotremes, and rapid for the X chromosome right after its formation. Although geneexpression evolution in mammals was strongly shaped......Changes in geneexpression are thought to underlie many of the phenotypic differences between species. However, large-scale analyses of geneexpression evolution were until recently prevented by technological limitations. Here we report the sequencing of polyadenylated RNA from six organs across...... ten species that represent all major mammalian lineages (placentals, marsupials and monotremes) and birds (the evolutionary outgroup), with the goal of understanding the dynamics of mammalian transcriptome evolution. We show that the rate of geneexpression evolution varies among organs, lineages...

Keywords: static security, geneexpression programming, probabilistic neural network ... Hence digital computers are usually installed in operations control centers to gather ...... power system protection, and applications of AI in power systems.

the development of adult brain in Drosophila melanogaster. C. R. VENKATESH ... vous system (CNS), at different time points during the pupal stage—a critical .... in frontal view, with further reduced reporter geneexpression. Orthodenticle and ...

stored at -80˚C in nuclease free water for geneexpression experiments. ..... So, identification of a unique signature for CAD globally as treatment target and early diagnostic biomarker needs ..... The colour of bar, blue, brown, grey and yellow.

Geneexpression and in vivo DNA binding data provide important information for understanding gene regulatory networks: in vivo DNA binding data indicate genomic regions where transcription factors are bound, and expression data show the output resulting from this binding. Thus, there must be functional relationships between these two types of data. While visualization and data analysis tools exist for each data type alone, there is a lack of tools that can easily explore the relationship between them. We propose an approach that uses the average expression driven by multiple of ciscontrol regions to visually relate geneexpression and in vivo DNA binding data. We demonstrate the utility of this tool with examples from the network controlling early Drosophila development. The results obtained support the idea that the level of occupancy of a transcription factor on DNA strongly determines the degree to which the factor regulates a target gene, and in some cases also controls whether the regulation is positive or negative.

Full Text Available BACKGROUND: Most eukaryotic genomes have undergone whole genome duplications during their evolutionary history. Recent studies have shown that the function of these duplicated genes can diverge from the ancestral gene via neo- or sub-functionalization within single genotypes. An additional possibility is that gene duplicates may also undergo partitioning of function among different genotypes of a species leading to genetic differentiation. Finally, the ability of gene duplicates to diverge may be limited by their biological function. METHODOLOGY/PRINCIPAL FINDINGS: To test these hypotheses, I estimated the impact of gene duplication and metabolic function upon intraspecific geneexpression variation of segmental and tandem duplicated genes within Arabidopsis thaliana. In all instances, the younger tandem duplicated genes showed higher intraspecific geneexpression variation than the average Arabidopsis gene. Surprisingly, the older segmental duplicates also showed evidence of elevated intraspecific geneexpression variation albeit typically lower than for the tandem duplicates. The specific biological function of the gene as defined by metabolic pathway also modulated the level of intraspecific geneexpression variation. The major energy metabolism and biosynthetic pathways showed decreased variation, suggesting that they are constrained in their ability to accumulate geneexpression variation. In contrast, a major herbivory defense pathway showed significantly elevated intraspecific variation suggesting that it may be under pressure to maintain and/or generate diversity in response to fluctuating insect herbivory pressures. CONCLUSION: These data show that intraspecific variation in geneexpression is facilitated by an interaction of gene duplication and biological activity. Further, this plays a role in controlling diversity of plant metabolism.

The white coat colour of sheep is an important economic trait. For unknown reasons, some animals are born with, and others develop with time, black skin spots that can also produce pigmented fibres. The presence of pigmented fibres in the white wool significantly decreases the fibre quality. The aim of this work was to study geneexpression in black spots (with and without pigmented fibres) and white skin by microarray techniques, in order to identify the possible genes involved in the development of this trait. Five unrelated Corriedale sheep were used and, for each animal, the three possible comparisons (three different hybridisations) between the three samples of interest were performed. Differential geneexpression patterns were analysed using different t-test approaches. Most of the major genes with well-known roles in skin pigmentation, e.g. ASIP, MC1R and C-KIT, showed no significant difference in the geneexpression between white skin and black spots. On the other hand, many of the differentially expressedgenes (raw P-value spots. The geneexpression of C-FOS and KLF4, transcription factors involved in the cellular response to external factors such as ultraviolet light, was validated by quantitative polymerase chain reaction (PCR). This exploratory study provides a list of candidate genes that could be associated with the development of black skin spots that should be studied in more detail. Characterisation of these genes will enable us to discern the molecular mechanisms involved in the development of this feature and, hence, increase our understanding of melanocyte biology and skin pigmentation. In sheep, understanding this phenomenon is a first step towards developing molecular tools to assist in the selection against the presence of pigmented fibres in white wool.

Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of geneexpression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 geneexpression datasets of the NCBI GeneExpression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

Full Text Available Glatopa™ is a generic glatiramer acetate recently approved for the treatment of patients with relapsing forms of multiple sclerosis. Geneexpression profiling was performed as a means to evaluate equivalence of Glatopa and Copaxone®. Microarray analysis containing 39,429 unique probes across the entire genome was performed in murine glatiramer acetate--responsive Th2-polarized T cells, a test system highly relevant to the biology of glatiramer acetate. A closely related but nonequivalent glatiramoid molecule was used as a control to establish assay sensitivity. Multiple probe-level (Student's t-test and sample-level (principal component analysis, multidimensional scaling, and hierarchical clustering statistical analyses were utilized to look for differences in geneexpression induced by the test articles. The analyses were conducted across all genes measured, as well as across a subset of genes that were shown to be modulated by Copaxone. The following observations were made across multiple statistical analyses: the expression of numerous genes was significantly changed by treatment with Copaxone when compared against media-only control; geneexpression profiles induced by Copaxone and Glatopa were not significantly different; and geneexpression profiles induced by Copaxone and the nonequivalent glatiramoid were significantly different, underscoring the sensitivity of the test system and the multiple analysis methods. Comparative analysis was also performed on sets of transcripts relevant to T-cell biology and antigen presentation, among others that are known to be modulated by glatiramer acetate. No statistically significant differences were observed between Copaxone and Glatopa in the expression levels (magnitude and direction of these glatiramer acetate-regulated genes. In conclusion, multiple methods consistently supported equivalent geneexpression profiles between Copaxone and Glatopa.

To investigate the general radiation-resistant mechanisms of bacteria, bioinformatic method was employed to predict highly expressedgenes for four radiation-resistant bacteria, i.e. Deinococcus geothermalis (D. geo), Deinococcus radiodurans (D. rad), Kineococcus radiotolerans (K. rad) and Rubrobacter xylanophilus (R. xyl). It is revealed that most of the three reference gene sets, i.e. ribosomal proteins, transcription factors and major chaperones, are generally highly expressed in the four ...

Background Simple clustering methods such as hierarchical clustering and k-means are widely used for geneexpression data analysis; but they are unable to deal with noise and high dimensionality associated with the microarray geneexpression data. Consensus clustering appears to improve the robustness and quality of clustering results. Incorporating prior knowledge in clustering process (semi-supervised clustering) has been shown to improve the consistency between the data partitioning and do...

Full Text Available BACKGROUND: In the field of neuroscience microarray geneexpression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal populations can in combination with global geneexpression profiling potentially increase the resolution and specificity of such studies to shed new light on neuronal functions at the cellular level. METHODOLOGY/PRINCIPAL FINDINGS: We examine the microarray geneexpression profiles of two distinct neuronal populations in the spinal cord of the neonatal rat, the principal motor neurons and specific interneurons involved in motor control. The geneexpression profiles of the respective cell populations were obtained from amplified mRNA originating from 50-250 fluorescently identified and laser microdissected cells. In the data analysis we combine a new microarray normalization procedure with a conglomerate measure of significant differential geneexpression. Using our methodology we find 32 genes to be more expressed in the interneurons compared to the motor neurons that all except one have not previously been associated with this neuronal population. As a validation of our method we find 17 genes to be more expressed in the motor neurons than in the interneurons and of these only one had not previously been described in this population. CONCLUSIONS/SIGNIFICANCE: We provide an optimized experimental protocol that allows isolation of gene transcripts from fluorescent retrogradely labeled cell populations in fresh tissue, which can be used to generate amplified aRNA for microarray hybridization from as few as 50 laser microdissected cells. Using this optimized experimental protocol in combination with our microarray analysis methodology we find 49 differentially expressedgenes between the motor neurons and the interneurons that reflect the functional

Background: Serial Analysis of GeneExpression ( SAGE) and microarrays have found awidespread application, but much ambiguity exists regarding the evaluation of these technologies. Cross-platform utilization of geneexpression data from the SAGE and microarray technology could reduce the need for

Full Text Available BACKGROUND: Production of proteins as therapeutic agents, research reagents and molecular tools frequently depends on expression in heterologous hosts. Synthetic genes are increasingly used for protein production because sequence information is easier to obtain than the corresponding physical DNA. Protein-coding sequences are commonly re-designed to enhance expression, but there are no experimentally supported design principles. PRINCIPAL FINDINGS: To identify sequence features that affect protein expression we synthesized and expressed in E. coli two sets of 40 genes encoding two commercially valuable proteins, a DNA polymerase and a single chain antibody. Genes differing only in synonymous codon usage expressed protein at levels ranging from undetectable to 30% of cellular protein. Using partial least squares regression we tested the correlation of protein production levels with parameters that have been reported to affect expression. We found that the amount of protein produced in E. coli was strongly dependent on the codons used to encode a subset of amino acids. Favorable codons were predominantly those read by tRNAs that are most highly charged during amino acid starvation, not codons that are most abundant in highly expressed E. coli proteins. Finally we confirmed the validity of our models by designing, synthesizing and testing new genes using codon biases predicted to perform well. CONCLUSION: The systematic analysis of gene design parameters shown in this study has allowed us to identify codon usage within a gene as a critical determinant of achievable protein expression levels in E. coli. We propose a biochemical basis for this, as well as design algorithms to ensure high protein production from synthetic genes. Replication of this methodology should allow similar design algorithms to be empirically derived for any expression system.

PURPOSE: A 128-gene signature has been proposed to predict outcome in patients with stages II and III colorectal cancers. In the present study, we aimed to reproduce and validate the 128-gene signature in external and independent material. METHODS: Geneexpression data from the original material...... were retrieved from the GeneExpression Omnibus (GEO) (n¿=¿111) in addition to a Danish data set (n¿=¿37). All patients had stages II and III colon cancers. A Prediction Analysis of Microarray classifier, based on the 128-gene signature and the original training set of stage I (n¿=¿65) and stage IV (n...... correctly predicted as stage IV-like, and the remaining patients were predicted as stage I-like and unclassifiable, respectively. Stage II patients could not be stratified. CONCLUSIONS: The 128-gene signature showed reproducibility in stage III colon cancer, but could not predict recurrence in stage II...

We have applied serial analysis of geneexpression for studying the molecular mechanism of the rat liver regeneration in the model of 70% partial hepatectomy. We generated three SAGE libraries from a normal control liver (NL library: 52,343 tags), from a sham control operated liver (Sham library: 51,028 tags), and from a regenerating liver (PH library: 53,061 tags). By SAGE bioinformatics analysis we identified 40 induced genes and 20 repressed genes during the liver regeneration. We verified temporal expression of such genes by real time PCR during the regeneration process and we characterized 13 induced genes and 3 repressed genes. We found connective tissue growth factor transcript and protein induced very early at 4 h after PH operation before hepatocytes proliferation is triggered. Our study suggests CTGF as a growth factor signaling mediator that could be involved directly in the mechanism of liver regeneration induction

Filoviruses subvert the human immune system in part by infecting and replicating in dendritic cells (DCs). Using gene arrays, a phenotypic profile of filovirus infection in human monocyte-derived DCs was assessed. Monocytes from human donors were cultured in GM-CSF and IL-4 and were infected with Ebola virus Kikwit variant for up to 48 h. Extracted DC RNA was analyzed on SuperArray's Dendritic and Antigen Presenting Cell Oligo GEArray and compared to uninfected controls. Infected DCs exhibited increased expression of cytokine, chemokine, antiviral, and anti-apoptotic genes not seen in uninfected controls. Significant increases of intracellular antiviral and MHC I and II genes were also noted in EBOV-infected DCs. However, infected DCs failed to show any significant difference in co-stimulatory T-cell geneexpression from uninfected DCs. Moreover, several chemokine genes were activated, but there was sparse expression of chemokine receptors that enabled activated DCs to home to lymph nodes. Overall, statistically significant expression of several intracellular antiviral genes was noted, which may limit viral load but fails to stop replication. EBOV geneexpression profiling is of vital importance in understanding pathogenesis and devising novel therapeutic treatments such as small-molecule inhibitors.

Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Geneexpression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Geneexpression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict geneexpression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real geneexpression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing geneexpression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

Changes in geneexpression after traditional Japanese massage therapy were investigated to clarify the mechanisms of the clinical effects of traditional Japanese massage therapy. This was a pilot experimental study. The study was conducted in a laboratory at Tsukuba University of Technology. The subjects were 2 healthy female volunteers (58-year-old Participant A, 55-year-old Participant B). The intervention consisted of a 40-minute full-body massage using standard traditional Japanese massage techniques through the clothing and a 40-minute rest as a control, in which participants lie on the massage table without being massaged. Before and after an intervention, blood was taken and analyzed by microarray: (1) The number of genes whose expression was more than double after the intervention than before was examined; (2) For those genes, gene ontology analysis identified statistically significant gene ontology terms. The geneexpression count in the total of 41,000 genes was 1256 genes for Participant A and 1778 for Participant B after traditional Japanese massage, and was 157 and 82 after the control, respectively. The significant gene ontology terms selected by both Participants A and B after massage were "immune response" and "immune system," whereas no gene ontology terms were selected by them in the control. It is implied that traditional Japanese massage therapy may affect the immune function. Further studies with more samples are necessary.

Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since geneexpression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in geneexpression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target geneexpression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of geneexpression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.

Highlights: • We have analysed geneexpression in the offspring of irradiated male mice. • CBA/Ca and BALB/c male mice were used in our study. • The pattern of geneexpression was established in four tissues. • Expression of genes in involved in rhythmic process/circadian rhythm is compromised. • Our data may explain the phenomenon of transgenerational genomic instability. - Abstract: The circadian system represents a complex network which influences the timing of many biological processes. Recent studies have established that circadian alterations play an important role in the susceptibility to many human diseases, including cancer. Here we report that paternal irradiation in mice significantly affects the expression of genes involved in rhythmic processes in their first-generation offspring. Using microarrays, the patterns of geneexpression were established for brain, kidney, liver and spleen samples from the non-exposed offspring of irradiated CBA/Ca and BALB/c male mice. The most over-represented categories among the genes differentially expressed in the offspring of control and irradiated males were those involved in rhythmic process, circadian rhythm and DNA-dependent regulation of transcription. The results of our study therefore provide a plausible explanation for the transgenerational effects of paternal irradiation, including increased transgenerational carcinogenesis described in other studies

Highlights: • We have analysed geneexpression in the offspring of irradiated male mice. • CBA/Ca and BALB/c male mice were used in our study. • The pattern of geneexpression was established in four tissues. • Expression of genes in involved in rhythmic process/circadian rhythm is compromised. • Our data may explain the phenomenon of transgenerational genomic instability. - Abstract: The circadian system represents a complex network which influences the timing of many biological processes. Recent studies have established that circadian alterations play an important role in the susceptibility to many human diseases, including cancer. Here we report that paternal irradiation in mice significantly affects the expression of genes involved in rhythmic processes in their first-generation offspring. Using microarrays, the patterns of geneexpression were established for brain, kidney, liver and spleen samples from the non-exposed offspring of irradiated CBA/Ca and BALB/c male mice. The most over-represented categories among the genes differentially expressed in the offspring of control and irradiated males were those involved in rhythmic process, circadian rhythm and DNA-dependent regulation of transcription. The results of our study therefore provide a plausible explanation for the transgenerational effects of paternal irradiation, including increased transgenerational carcinogenesis described in other studies.

Cellular responses to damages from ionizing radiation (IR) exposure are influenced not only by the genes involved in DNA double strand break (DSB) repair, but also by non- DSB repair genes. We demonstrated previously that suppressed expression of several non-DSB repair genes, such as XPA, elevated IR-induced cytogenetic damages. In the present study, we exposed human fibroblasts that were treated with control or XPA targeting siRNA to 250 MeV protons (0 to 4 Gy), and analyzed chromosome aberrations and expressions of genes involved in DNA repair. As expected, after proton irradiation, cells with suppressed expression of XPA showed a significantly elevated frequency of chromosome aberrations compared with control siRNA treated (CS) cells. Protons caused more severe DNA damages in XPA knock-down cells, as 36% cells contained multiple aberrations compared to 25% in CS cells after 4Gy proton irradiation. Comparison of geneexpressions using the real-time PCR array technique revealed that expressions of p53 and its regulated genes in irradiated XPA suppressed cells were altered similarly as in CS cells, suggesting that the impairment of IR induced DNA repair in XPA suppressed cells is p53-independent. Except for XPA, which was more than 2 fold down regulated in XPA suppressed cells, several other DNA damage sensing and repair genes (GTSE1, RBBP8, RAD51, UNG and XRCC2) were shown a more than 1.5 fold difference between XPA knock-down cells and CS cells after proton exposure. The possible involvement of these genes in the impairment of DNA repair in XPA suppressed cells will be further investigated.

textabstractWe have used transgenic mice to study the influence of position of the human globin genes relative to the locus control region (LCR) on their expression pattern during development. The LCR, which is located 5' of the globin gene cluster, is normally required for the activation of all the

Normal Nasal GeneExpression Levels Using cDNA Array Technology. The nasal epithelium is a target site for chemically-induced toxicity and carcinogenicity. To detect and analyze genetic events which contribute to nasal tumor development, we first defined the gene expressi...

We investigated correlated responses in the transcriptomes of longevity-selected lines of Drosophila melanogaster to identify pathways that affect life span in metazoan systems. We evaluated the geneexpression profile in young, middle-aged, and old male flies, finding that 530 genes were...

Chicken lines differ in genetic disease susceptibility. The scope of the research described in this thesis was to identify genes involved in genetic disease resistance in the chicken intestine. Therefore geneexpression in the jejunum was investigated using a microarray approach. An intestine

Full Text Available Microarray-based geneexpression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of geneexpression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressedgenes for creation of potential metagenes, 3 association with outcome for geneexpression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

Full Text Available Kashin-Beck Disease (KBD is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published geneexpression profile data on cartilage and peripheral blood mononuclear cells (PBMCs from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A geneexpression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR algorithm and support vector machine (SVM algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD.

Microarrays offer biologists an exciting tool that allows the simultaneous assessment of geneexpression levels for thousands of genes at once. At the time of their inception, microarrays were hailed as the new dawn in cancer biology and oncology practice with the hope that within a decade diseases

Several clustering and biclustering methods have been introduced to analyze the geneexpression data by identifying the similar patterns and grouping genes into subsets that share biological significance. However, it is not clear how the different methods compare with each other with respect to the biological relevance of ...

Serial analysis of geneexpression (SAGE) was used to identify genes that might be involved in the development or growth of medulloblastoma, a childhood brain tumor. Sequence tags from medulloblastoma (10229) and fetal brain (10692) were determined. The distributions of sequence tags in each

Geneexpression has been used to identify disease gene biomarkers, but there are ongoing challenges. Single gene or gene-set biomarkers are inadequate to provide sufficient understanding of complex disease mechanisms and the relationship among those genes. Network-based methods have thus been considered for inferring the interaction within a group of genes to further study the disease mechanism. Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account of network topology. However, its performance relies on a greedy search for building subnetworks and thus requires further improvement. In this work, we establish a new approach named Gene Sub-Network-based Feature Selection (GSNFS) by implementing the GNFS framework with two proposed searching and scoring algorithms, namely gene-set-based (GS) search and parent-node-based (PN) search, to identify subnetworks. An additional dataset is used to validate the results. The two proposed searching algorithms of the GSNFS method for subnetwork expansion are concerned with the degree of connectivity and the scoring scheme for building subnetworks and their topology. For each iteration of expansion, the neighbour genes of a current subnetwork, whose expression data improved the overall subnetwork score, is recruited. While the GS search calculated the subnetwork score using an activity score of a current subnetwork and the geneexpression values of its neighbours, the PN search uses the expression value of the corresponding parent of each neighbour gene. Four lung cancer expression datasets were used for subnetwork identification. In addition, using pathway data and protein-protein interaction as network data in order to consider the interaction among significant genes were discussed. Classification was performed to compare the performance of the identified gene subnetworks with three

We have previously demonstrated that alcohol exposure at early neurulation induces growth retardation, neural tube abnormalities, and alteration of DNA methylation. To explore the global geneexpression changes which may underline these developmental defects, microarray analyses were performed in a whole embryo mouse culture model that allows control over alcohol and embryonic variables. Alcohol caused teratogenesis in brain, heart, forelimb, and optic vesicle; a subset of the embryos also showed cranial neural tube defects. In microarray analysis (accession number GSM9545), adopting hypothesis-driven Gene Set Enrichment Analysis (GSEA) informatics and intersection analysis of two independent experiments, we found that there was a collective reduction in expression of neural specification genes (neurogenin, Sox5, Bhlhe22), neural growth factor genes [Igf1, Efemp1, Klf10 (Tieg), and Edil3], and alteration of genes involved in cell growth, apoptosis, histone variants, eye and heart development. There was also a reduction of retinol binding protein 1 (Rbp1), and de novo expression of aldehyde dehydrogenase 1B1 (Aldh1B1). Remarkably, four key hematopoiesis genes (glycophorin A, adducin 2, beta-2 microglobulin, and ceruloplasmin) were absent after alcohol treatment, and histone variant genes were reduced. The down-regulation of the neurospecification and the neurotrophic genes were further confirmed by quantitative RT-PCR. Furthermore, the geneexpression profile demonstrated distinct subgroups which corresponded with two distinct alcohol-related neural tube phenotypes: an open (ALC-NTO) and a closed neural tube (ALC-NTC). Further, the epidermal growth factor signaling pathway and histone variants were specifically altered in ALC-NTO, and a greater number of neurotrophic/growth factor genes were down-regulated in the ALC-NTO than in the ALC-NTC embryos. This study revealed a set of genes vulnerable to alcohol exposure and genes that were associated with neural tube

Full Text Available Abstract Background Legumes (Leguminosae or Fabaceae play a major role in agriculture. Transcriptomics studies in the model legume species, Medicago truncatula, are instrumental in helping to formulate hypotheses about the role of legume genes. With the rapid growth of publically available Affymetrix GeneChip Medicago Genome Array GeneChip data from a great range of tissues, cell types, growth conditions, and stress treatments, the legume research community desires an effective bioinformatics system to aid efforts to interpret the Medicago genome through functional genomics. We developed the Medicago truncatula GeneExpression Atlas (MtGEA web server for this purpose. Description The Medicago truncatula GeneExpression Atlas (MtGEA web server is a centralized platform for analyzing the Medicago transcriptome. Currently, the web server hosts geneexpression data from 156 Affymetrix GeneChip® Medicago genome arrays in 64 different experiments, covering a broad range of developmental and environmental conditions. The server enables flexible, multifaceted analyses of transcript data and provides a range of additional information about genes, including different types of annotation and links to the genome sequence, which help users formulate hypotheses about gene function. Transcript data can be accessed using Affymetrix probe identification number, DNA sequence, gene name, functional description in natural language, GO and KEGG annotation terms, and InterPro domain number. Transcripts can also be discovered through co-expression or differential expression analysis. Flexible tools to select a subset of experiments and to visualize and compare expression profiles of multiple genes have been implemented. Data can be downloaded, in part or full, in a tabular form compatible with common analytical and visualization software. The web server will be updated on a regular basis to incorporate new geneexpression data and genome annotation, and is accessible

Background: RNA-sequencing (RNA-seq) is a powerful technique for the identification of genetic variants that affect gene-expression levels, either through expression quantitative trait locus (eQTL) mapping or through allele-specific expression (ASE) analysis. Given increasing numbers of RNA-seq

pL2 plasmid isolated from E. coli was introduced into S. salivarius subsp. thermophilus and Lactococcus lactis cells by electro-transformation. The lysozyme enzymes expressing by these bacteria were found to be active on Micrococcus luteus cells and thereby preventing their growth on assay plates. Thermostability of ...

Expressed Satisfaction with the Nominal Group Technique Among Change Agents. Jon Neal Gresham The purpose of this study was to determine whether or not policymakers and change agents with differing professional backgrounds and responsibilities, who participated in the structured process of a

Full Text Available There is a revolution in the ability to analyze geneexpression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional geneexpression space. One open question is whether cell types form discrete clusters or whether geneexpression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes in geneexpression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in geneexpression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a

Full Text Available Our search for genes related to cell wall metabolism in the sugarcane expressed sequence tag (SUCEST database (http://sucest.lbi.dcc.unicamp.br resulted in 3,283 reads (1% of the total reads which were grouped into 459 clusters (potential genes with an average of 7.1 reads per cluster. To more clearly display our correlation coefficients, we constructed surface maps which we used to investigate the relationship between cell wall genes and the sugarcane tissues libraries from which they came. The only significant correlations that we found between cell wall genes and/or their expression within particular libraries were neutral or synergetic. Genes related to cellulose biosynthesis were from the CesA family, and were found to be the most abundant cell wall related genes in the SUCEST database. We found that the highest number of CesA reads came from the root and stem libraries. The genes with the greatest number of reads were those involved in cell wall hydrolases (e.g. beta-1,3-glucanases, xyloglucan endo-beta-transglycosylase, beta-glucosidase and endo-beta-mannanase. Correlation analyses by surface mapping revealed that the expression of genes related to biosynthesis seems to be associated with the hydrolysis of hemicelluloses, pectin hydrolases being mainly associated with xyloglucan hydrolases. The patterns of cell wall related geneexpression in sugarcane based on the number of reads per cluster reflected quite well the expected physiological characteristics of the tissues. This is the first work to provide a general view on plant cell wall metabolism through the expression of related genes in almost all the tissues of a plant at the same time. For example, developing flowers behaved similarly to both meristematic tissues and leaf-root transition zone tissues. Besides providing a basis for future research on the mechanisms of plant development which involve the cell wall, our findings will provide valuable tools for plant engineering in the

May 16, 2011 ... from fatty acid synthase (FAS) with a different glucose level in ... By using the following formula, this study was able to quantify the mRNA expression of ... hypertension, heart disease and diabetes. ... regulation of geneexpression has emerged in recent ... stages of adipocyte meta-bolism are relatively well.

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in geneexpression

These results suggest that the aberrant of geneexpression patterns detected in the oocytes of NOs compared with COCs explains their reduced quality in terms of development and maturation. In conclusion, these differentially expressed mRNAs may be involved in cellular interactions between oocytes and cumulus cells ...

Study on the characteristics of integration and expression is the basis of genetic stability of foreign genes in transgenic trees. To obtain insight into the relationship of transgene copy number and expression level, we screened 22 transgenic birch lines. Southern blot analysis of the transgenic birch plants indicated that the ...

BACKGROUND: No reliable biomarker for metastatic potential in the risk stratification of papillary thyroid carcinoma exists. We aimed to develop a gene-expression classifier for metastatic potential. MATERIALS AND METHODS: Genome-wide expression analyses were used. Development cohort: freshly...

co-transfer of DNAs to cells was monitored by analyzing transient gus expression 24 h after .... induction frequency was determined by measuring the ... Effect of age on transient expression of gus gene and production of hygromycin .... japonica varieties via electric discharge particle acceleration of .... yellow stem borer.

Low temperature is one of the main abiotic stresses affecting rice yield in Chile. Alterations in phenology and physiology of the crop are observed after a cold event. The objective of this work was to study the relative expression of genes related with cold stress in Chilean cultivars of rice. For this, we analyzed the expression ...

Aug 4, 2009 ... Study on the characteristics of integration and expression is the basis of genetic stability of foreign genes in transgenic trees. To obtain insight into the relationship of transgene copy number and expression level, we screened 22 transgenic birch lines. Southern blot analysis of the transgenic birch.

Full Text Available Large-scale transcriptional studies aim to decipher the dynamic cellular responses to a stimulus, like different environmental conditions. In the era of high-throughput omics biology, the most used technologies for these purposes are microarray and RNA-Seq, whose data are usually required to be deposited in public repositories upon publication. Such repositories have the enormous potential to provide a comprehensive view of how different experimental conditions lead to expression changes, by comparing geneexpression across all possible measured conditions. Unfortunately, this task is greatly impaired by differences among experimental platforms that make direct comparisons difficult.In this paper we present the Vitis Expression Studies Platform Using COLOMBOS Compendia Instances (VESPUCCI, a geneexpression compendium for grapevine which was built by adapting an approach originally developed for bacteria, and show how it can be used to investigate complex geneexpression patterns. We integrated nearly all publicly available microarray and RNA-Seq expression data: 1608 geneexpression samples from 10 different technological platforms. Each sample has been manually annotated using a controlled vocabulary developed ad hoc to ensure both human readability and computational tractability. Expression data in the compendium can be visually explored using several tools provided by the web interface or can be programmatically accessed using the REST interface. VESPUCCI is freely accessible at http://vespucci.colombos.fmach.it.

Full Text Available Abstract Background Microarray technology is a widely used approach for monitoring genome-wide geneexpression. For Arabidopsis, there are over 1,800 microarray hybridizations representing many different experimental conditions on Affymetrix™ ATH1 gene chips alone. This huge amount of data offers a unique opportunity to infer the principles that govern the regulation of geneexpression in plants. Results We used bioinformatics methods to analyze publicly available data obtained using the ATH1 chip from Affymetrix. A total of 1887 ATH1 hybridizations were normalized and filtered to eliminate low-quality hybridizations. We classified and compared control and treatment hybridizations and determined differential geneexpression. The largest differences in geneexpression were observed when comparing samples obtained from different organs. On average, ten-fold more genes were differentially expressed between organs as compared to any other experimental variable. We defined "gene responsiveness" as the number of comparisons in which a gene changed its expression significantly. We defined genes with the highest and lowest responsiveness levels as hypervariable and housekeeping genes, respectively. Remarkably, housekeeping genes were best distinguished from hypervariable genes by differences in methylation status in their transcribed regions. Moreover, methylation in the transcribed region was inversely correlated (R2 = 0.8 with gene responsiveness on a genome-wide scale. We provide an example of this negative relationship using genes encoding TCA cycle enzymes, by contrasting their regulatory responsiveness to nitrate and methylation status in their transcribed regions. Conclusion Our results indicate that the Arabidopsis transcriptome is largely established during development and is comparatively stable when faced with external perturbations. We suggest a novel functional role for DNA methylation in the transcribed region as a key determinant

Biotechnology is an effective and important method of improving both quality and agronomic traits in rice. We are developing novel molecular tools for genetic engineering, with a focus on developing novel transgene expression control elements (i.e. promoters) for rice. A suite of monocot grass promo...

-378), the expression patterns of various functional genes (with an emphasis on nif genes involved in N2-fixation), the protein levels of nitrogenase (NifH), the N2-fixation activity, as well as microsensor based measurements on O2 availability, production and consumption were investigated in situ over the entire diel...... cycle. Interestingly, it was found that while the nif genes are expressed, and nitrogenase is synthesized once the mat gets anoxic in the early evening, the largest N2-fixation activity occurs as a burst during dim light in the early morning, albeit protein levels remained high over the entire course...

Set-level classification of geneexpression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional vectors of features corresponding to biologically interpretable gene sets. The dimensionality reduction brings the promise of a decreased risk of overfitting, potentially resulting in improved accuracy of the learned classifiers. However, recent empirical research has not confirmed this expectation. Here we hypothesize that the reported unfavorable classification results in the set-level framework were due to the adoption of unsuitable gene sets defined typically on the basis of the Gene ontology and the KEGG database of metabolic networks. We explore an alternative approach to defining gene sets, based on regulatory interactions, which we expect to collect genes with more correlated expression. We hypothesize that such more correlated gene sets will enable to learn more accurate classifiers. We define two families of gene sets using information on regulatory interactions, and evaluate them on phenotype-classification tasks using public prokaryotic geneexpression data sets. From each of the two gene-set families, we first select the best-performing subtype. The two selected subtypes are then evaluated on independent (testing) data sets against state-of-the-art gene sets and against the conventional gene-level approach. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. Novel gene sets defined on the basis of regulatory interactions improve set-level classification of geneexpression data. The experimental scripts and other material needed to reproduce the experiments are available at http://ida.felk.cvut.cz/novelgenesets.tar.gz.

Full Text Available Abstract Background In food production animals, especially cattle, the diagnosis of gestation is important because the timing of gestation directly affects the running of farms. Various methods have been used to detect gestation, but none of them are ideal because of problems with the timing of detection or the accuracy, simplicity, or cost of the method. A new method for detecting gestation, which involves assessing interferon-tau (IFNT-stimulated geneexpression in peripheral blood leukocytes (PBL, was recently proposed. PBL fractionation methods were used to examine whether the expression profiles of various PBL populations could be used as reliable diagnostic markers of bovine gestation. Methods PBL were collected on days 0 (just before artificial insemination, 7, 14, 17, 21, and 28 of gestation. The geneexpression levels of the PBL were assessed with microarray analysis and/or quantitative real-time reverse transcription (q PCR. PBL fractions were collected by flow cytometry or density gradient cell separation using Histopaque 1083 or Ficoll-Conray solutions. The expression levels of four IFNT-stimulated genes, interferon-stimulated protein 15 kDa (ISG15, myxovirus-resistance (MX 1 and 2, and 2′-5′-oligoadenylate synthetase (OAS1, were then analyzed in each fraction through day 28 of gestation using qPCR. Results Microarray analysis detected 72 and 28 genes in whole PBL that were significantly higher on days 14 and 21 of gestation, respectively, than on day 0. The upregulated genes included IFNT-stimulated genes. The expression levels of these genes increased with the progression of gestation until day 21. In flow cytometry experiments, on day 14 the expression levels of all of the genes were significantly higher in the granulocyte fraction than in the other fractions. Their expression gradually decreased through day 28 of gestation. Strong correlations were observed between the expression levels of the four genes in the granulocyte

Digital anatomical atlases are increasingly used in order to depict different geneexpression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of geneexpression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in geneexpression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered geneexpression patterns has been generated for the anterior part (episphere) of the Platynereis trochophore larva and used for the detailed study of neuronal development. Here we introduce and evaluate a method for whole-body geneexpression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2'-thiodiethanol (TDE), which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP) in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4'6-diamidino-2-phenylindole (DAPI). Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental stage. We then registered to these templates the

Full Text Available Abstract Background Digital anatomical atlases are increasingly used in order to depict different geneexpression patterns and neuronal morphologies within a standardized reference template. In evo-devo, a discipline in which the comparison of geneexpression patterns is a widely used approach, such standardized anatomical atlases would allow a more rigorous assessment of the conservation of and changes in geneexpression patterns during micro- and macroevolutionary time scales. Due to its small size and invariant early development, the annelid Platynereis dumerilii is particularly well suited for such studies. Recently a reference template with registered geneexpression patterns has been generated for the anterior part (episphere of the Platynereis trochophore larva and used for the detailed study of neuronal development. Results Here we introduce and evaluate a method for whole-body geneexpression pattern registration for Platynereis trochophore and nectochaete larvae based on whole-mount in situ hybridization, confocal microscopy, and image registration. We achieved high-resolution whole-body scanning using the mounting medium 2,2’-thiodiethanol (TDE, which allows the matching of the refractive index of the sample to that of glass and immersion oil thereby reducing spherical aberration and improving depth penetration. This approach allowed us to scan entire whole-mount larvae stained with nitroblue tetrazolium/5-bromo-4-chloro-3-indolyl phosphate (NBT/BCIP in situ hybridization and counterstained fluorescently with an acetylated-tubulin antibody and the nuclear stain 4’6-diamidino-2-phenylindole (DAPI. Due to the submicron isotropic voxel size whole-mount larvae could be scanned in any orientation. Based on the whole-body scans, we generated four different reference templates by the iterative registration and averaging of 40 individual image stacks using either the acetylated-tubulin or the nuclear-stain signal for each developmental

The aim of this study was to investigate changes in geneexpression after tactile stimulation (tickling) accompanied by positive emotion in the adolescent rat brain. We observed a positive emotional response (50-kHz ultrasonic vocalizations) after tickling using a modified version of the Panksepp method, and then comprehensively compared geneexpression levels in the hypothalamus of the tickled rats and control rats using the microarray technique. After 4 weeks of stimulation, the expression levels of 321 of the 41,012 genes (including transcripts) were changed; 136 genes were up-regulated (>1.5-fold) and 185 were down-regulated (>0.67-fold) in the tickled rat group. Upon ontology analysis, the up-regulated genes were assigned to the following Gene Ontology (GO) terms: feeding behavior, neuropeptide signaling pathway, biogenic amine biosynthesis and catecholamine biosynthesis. Down-regulated genes were not assigned to any GO term categorized as a biological process. In conclusion, repeated tickling stimulation with positive emotion affected neuronal circuitry directly and/or indirectly, and altered the expression of genes related to the regulation of feeding in the adolescent rat hypothalamus.

Full Text Available Abstract Background Carcinogenesis is a multi-step process indicated by several genes up- or down-regulated during tumor progression. This study examined and identified differentially expressedgenes in cutaneous squamous cell carcinoma (SCC. Results Three different biopsies of 5 immunosuppressed organ-transplanted recipients each normal skin (all were pooled, actinic keratosis (AK (two were pooled, and invasive SCC and additionally 5 normal skin tissues from immunocompetent patients were analyzed. Thus, total RNA of 15 specimens were used for hybridization with Affymetrix HG-U133A microarray technology containing 22,283 genes. Data analyses were performed by prediction analysis of microarrays using nearest shrunken centroids with the threshold 3.5 and ANOVA analysis was independently performed in order to identify differentially expressedgenes (p vs. AK and SCC were observed for 118 genes. Conclusion The majority of identified differentially expressedgenes in cutaneous SCC were previously not described.

Full Text Available We present the AGEMAP (Atlas of GeneExpression in Mouse Aging Project geneexpression database, which is a resource that catalogs changes in geneexpression as a function of age in mice. The AGEMAP database includes expression changes for 8,932 genes in 16 tissues as a function of age. We found great heterogeneity in the amount of transcriptional changes with age in different tissues. Some tissues displayed large transcriptional differences in old mice, suggesting that these tissues may contribute strongly to organismal decline. Other tissues showed few or no changes in expression with age, indicating strong levels of homeostasis throughout life. Based on the pattern of age-related transcriptional changes, we found that tissues could be classified into one of three aging processes: (1 a pattern common to neural tissues, (2 a pattern for vascular tissues, and (3 a pattern for steroid-responsive tissues. We observed that different tissues age in a coordinated fashion in individual mice, such that certain mice exhibit rapid aging, whereas others exhibit slow aging for multiple tissues. Finally, we compared the transcriptional profiles for aging in mice to those from humans, flies, and worms. We found that genes involved in the electron transport chain show common age regulation in all four species, indicating that these genes may be exceptionally good markers of aging. However, we saw no overall correlation of age regulation between mice and humans, suggesting that aging processes in mice and humans may be fundamentally different.

Full Text Available Abstract Background The degree of conservation of geneexpression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Results Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Conclusions Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

The degree of conservation of geneexpression between homologous organs largely remains an open question. Several recent studies reported some evidence in favor of such conservation. Most studies compute organs' similarity across all orthologous genes, whereas the expression level of many genes are not informative about organ specificity. Here, we use a modularization algorithm to overcome this limitation through the identification of inter-species co-modules of organs and genes. We identify such co-modules using mouse and human microarray expression data. They are functionally coherent both in terms of genes and of organs from both organisms. We show that a large proportion of genes belonging to the same co-module are orthologous between mouse and human. Moreover, their zebrafish orthologs also tend to be expressed in the corresponding homologous organs. Notable exceptions to the general pattern of conservation are the testis and the olfactory bulb. Interestingly, some co-modules consist of single organs, while others combine several functionally related organs. For instance, amygdala, cerebral cortex, hypothalamus and spinal cord form a clearly discernible unit of expression, both in mouse and human. Our study provides a new framework for comparative analysis which will be applicable also to other sets of large-scale phenotypic data collected across different species.

Despite evidence for adaptive changes in both geneexpression and non-protein-coding, putatively regulatory regions of the genome during human evolution, the relationship between geneexpression and adaptive changes in cis-regulatory regions remains unclear. Here we present new measurements of geneexpression in five tissues of humans and chimpanzees, and use them to assess this relationship. We then compare our results with previous studies of adaptive noncoding changes, analyzing correlations at the level of gene ontology groups, in order to gain statistical power to detect correlations. Consistent with previous studies, we find little correlation between geneexpression and adaptive noncoding changes at the level of individual genes; however, we do find significant correlations at the level of biological function ontology groups. The types of function include processes regulated by specific transcription factors, responses to genetic or chemical perturbations, and differentiation of cell types within the immune system. Among functional categories co-enriched with both differential expression and noncoding adaptation, prominent themes include cancer, particularly epithelial cancers, and neural development and function.

Dihydroflavonol 4-reductase (DFR) genes from Rosa chinensis (Asn type) and Calibrachoa hybrida (Asp type), driven by a CaMV 35S promoter, were integrated into the petunia (Petunia hybrida) cultivar 9702. Exogenous DFR geneexpression characteristics were similar to flower-color changes, and effects on anthocyanin concentration were observed in both types of DFR gene transformants. Expression analysis showed that exogenous DFR genes were expressed in all of the tissues, but the expression levels were significantly different. However, both of them exhibited a high expression level in petals that were starting to open. The introgression of DFR genes may significantly change DFR enzyme activity. Anthocyanin ultra-performance liquid chromatography results showed that anthocyanin concentrations changed according to DFR enzyme activity. Therefore, the change in flower color was probably the result of a DFR enzyme change. Pelargonidin 3-O-glucoside was found in two different transgenic petunias, indicating that both CaDFR and RoDFR could catalyze dihydrokaempferol. Our results also suggest that transgenic petunias with DFR gene of Asp type could biosynthesize pelargonidin 3-O-glucoside.

Full Text Available Forkhead box (Fox genes code for transcription factors that play important roles in different biological processes. They are found in a wide variety of organisms and appeared in unicellular eukaryotes. In metazoans, the gene family includes many members that can be subdivided into 24 classes. Cephalochordates are key organisms to understand the functional evolution of gene families in the chordate lineage due to their phylogenetic position as an early divergent chordate, their simple anatomy and genome structure. In the genome of the cephalochordate amphioxus Branchiostoma floridae, 32 Fox genes were identified, with at least one member for each of the classes that were present in the ancestor of bilaterians. In this work we describe the expression pattern of 13 of these genes during the embryonic development of the Mediterranean amphioxus, Branchiostoma lanceolatum. We found that FoxK and FoxM genes present an ubiquitous expression while all the others show specific expression patterns restricted to diverse embryonic territories. Many of these expression patterns are conserved with vertebrates, suggesting that the main functions of Fox genes in chordates were present in their common ancestor.

Most of the existing methods for the identification of biologically interesting genes in a temporal expression profiling dataset do not fully exploit the temporal ordering in the dataset and are based on normality assumptions for the geneexpression. In this paper, we introduce a Bayesian median regression model to detect genes whose temporal profile is significantly different across a number of biological conditions. The regression model is defined by a polynomial function where both time and condition effects as well as interactions between the two are included. MCMC-based inference returns the posterior distribution of the polynomial coefficients. From this a simple Bayes factor test is proposed to test for significance. The estimation of the median rather than the mean, and within a Bayesian framework, increases the robustness of the method compared to a Hotelling T2-test previously suggested. This is shown on simulated data and on muscular dystrophy geneexpression data.

Bladder cancer is a common cancer worldwide and its incidence continues to increase. There are approximately 261,000 cases of bladder cancer resulting in 115,000 deaths annually. This study aimed to integrate bladder cancer genome copy number variation information and bladder cancer gene transcription level expression data to construct a causal-target module network of the range of bladder cancer-related genomes. Here, we explored the control mechanism underlying bladder cancer phenotype expression regulation by the major bladder cancer genes. We selected 22 modules as the initial module network to expand the search to screen more networks. After bootstrapping 100 times, we obtained 16 key regulators. These 16 key candidate regulatory genes were further expanded to identify the expression changes of 11,676 genes in 275 modules, which may all have the same regulation. In conclusion, a series of modules associated with the terms 'cancer' or 'bladder' were considered to constitute a potential network.

Full Text Available Males and females have a variety of sexually dimorphic traits, most of which result from hormonal differences. However, differences between male and female embryos initiate very early in development, before hormonal influence begins, suggesting the presence of genetically driven sexual dimorphisms. By comparing the geneexpression profiles of male and X-inactivated female human pluripotent stem cells, we detected Y-chromosome-driven effects. We discovered that the sex-determining gene SRY is expressed in human male pluripotent stem cells and is induced by reprogramming. In addition, we detected more than 200 differentially expressed autosomal genes in male and female embryonic stem cells. Some of these genes are involved in steroid metabolism pathways and lead to sex-dependent differentiation in response to the estrogen precursor estrone. Thus, we propose that the presence of the Y chromosome and specifically SRY may drive sex-specific differences in the growth and differentiation of pluripotent stem cells.

Full Text Available It is well established that geneexpression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on geneexpression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related geneexpression alterations. In humans, many more genes undergo consistent expression changes in the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.

There has been a growing interest in identifying context-specific active protein-protein interaction (PPI) subnetworks through integration of PPI and time course geneexpression data. However the interaction dynamics during the biological process under study has not been sufficiently considered previously. Here we propose a topology-phase locking (TopoPL) based scoring metric for identifying active PPI subnetworks from time series expression data. First the temporal coordination in geneexpression changes is evaluated through phase locking analysis; The results are subsequently integrated with PPI to define an activity score for each PPI subnetwork, based on individual member expression, as well topological characteristics of the PPI network and of the expression temporal coordination network; Lastly, the subnetworks with the top scores in the whole PPI network are identified through simulated annealing search. Application of TopoPL to simulated data and to the yeast cell cycle data showed that it can more sensitively identify biologically meaningful subnetworks than the method that only utilizes the static PPI topology, or the additive scoring method. Using TopoPL we identified a core subnetwork with 49 genes important to yeast cell cycle. Interestingly, this core contains a protein complex known to be related to arrangement of ribosome subunits that exhibit extremely high geneexpression synchronization. Inclusion of interaction dynamics is important to the identification of relevant gene networks.

Full Text Available The identification of transcription factor binding sites is essential to the understanding of the regulation of geneexpression and the reconstruction of genetic regulatory networks. The in silico identification of cis-regulatory motifs is challenging due to sequence variability and lack of sufficient data to generate consensus motifs that are of quantitative or even qualitative predictive value. To determine functional motifs in geneexpression, we propose a strategy to adopt false discovery rate (FDR and estimate motif effects to evaluate combinatorial analysis of motif candidates and temporal geneexpression data. The method decreases the number of predicted motifs, which can then be confirmed by genetic analysis. To assess the method we used simulated motif/expression data to evaluate parameters. We applied this approach to experimental data for a group of iron responsive genes in Salmonella typhimurium 14028S. The method identified known and potentially new ferric-uptake regulator (Fur binding sites. In addition, we identified uncharacterized functional motif candidates that correlated with specific patterns of expression. A SAS code for the simulation and analysis geneexpression data is available from the first author upon request.

It is well established that geneexpression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on geneexpression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related geneexpression alterations. In humans, many more genes undergo consistent expression changes in the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.

Full Text Available Abstract Background DNA microarrays are widely used in geneexpression analyses. To increase throughput and minimize costs without reducing geneexpression data obtained, we investigated whether four mRNA samples can be analyzed simultaneously by applying four different fluorescent dyes. Results Following tests for cross-talk of fluorescence signals, Alexa 488, Alexa 594, Cyanine 3 and Cyanine 5 were selected for hybridizations. For self-hybridizations, a single RNA sample was labelled with all dyes and hybridized on commercial cDNA arrays or on in-house spotted oligonucleotide arrays. Correlation coefficients for all combinations of dyes were above 0.9 on the cDNA array. On the oligonucleotide array they were above 0.8, except combinations with Alexa 488, which were approximately 0.5. Standard deviation of expression differences for replicate spots were similar on the cDNA array for all dye combinations, but on the oligonucleotide array combinations with Alexa 488 showed a higher variation. Conclusion In conclusion, the four dyes can be used simultaneously for geneexpression experiments on the tested cDNA array, but only three dyes can be used on the tested oligonucleotide array. This was confirmed by hybridizations of control with test samples, as all combinations returned similar numbers of differentially expressedgenes with comparable effects on geneexpression.

Background: In the field of neuroscience microarray geneexpression profiles on anatomically defined brain structures are being used increasingly to study both normal brain functions as well as pathological states. Fluorescent tracing techniques in brain tissue that identifies distinct neuronal p...

Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group...... clinical courses, and they may be useful as novel prognostic biomarkers in breast cancer. The aim of the present project was to predict the development of metastasis in lymph node negative breast cancer patients by RNA profiling. We collected and analyzed 82 primary breast tumors from patients who...... and the time of event. Previous findings have shown that high expression of the lncRNA HOTAIR is correlated with poor survival in breast cancer. We validated this finding by demonstrating that high HOTAIR expression in our primary tumors was significantly associated with worse prognosis independent...

Real-time quantitative RT-PCR analysis of laser microdissected tissue is considered the most accurate technique for determining tissue geneexpression. The discovery of estrogen receptor beta (ERbeta) has focussed renewed interest on the role of estrogen receptors in prostate cancer, yet few studies have utilized the technique to analyze estrogen receptor geneexpression in prostate cancer. Fresh tissue was obtained from 11 radical prostatectomy specimens and from 6 patients with benign prostate hyperplasia. Pure populations of benign and malignant prostate epithelium were laser microdissected, followed by RNA isolation and electrophoresis. Quantitative RT-PCR was performed using primers for androgen receptor (AR), estrogen receptor beta (ERbeta), estrogen receptor alpha (ERalpha), progesterone receptor (PGR) and prostate specific antigen (PSA), with normalization to two housekeeping genes. Differences in geneexpression were analyzed using the Mann-Whitney U-test. Correlation coefficients were analyzed using Spearman's test. Significant positive correlations were seen when AR and AR-dependent PSA, and ERalpha and ERalpha-dependent PGR were compared, indicating a representative population of RNA transcripts. ERbeta geneexpression was significantly over-expressed in the cancer group compared with benign controls (P cancer group (P prostate cancer specimens. In concert with recent studies the findings suggest differential production of ERbeta splice variants, which may play important roles in the genesis of prostate cancer. (c) 2009 Wiley-Liss, Inc.

Molecular biology provides the ability to implement forms of information and network security completely outside the bounds of legacy security protocols and algorithms. This paper addresses an approach which instantiates the power of geneexpression for security. Molecular biology provides a rich source of geneexpression and regulation mechanisms, which can be adopted to use in the information and electronic communication domains. Conventional security protocols are becoming increasingly vulnerable due to more intensive, highly capable attacks on the underlying mathematics of cryptography. Security protocols are being undermined by social engineering and substandard implementations by IT organizations. Molecular biology can provide countermeasures to these weak points with the current security approaches. Future advances in instruments for analyzing assays will also enable this protocol to advance from one of cryptographic algorithms to an integrated system of cryptographic algorithms and real-time expression and assay of geneexpression products.

In bacteria, the rate of cell proliferation and the level of geneexpression are intimately intertwined. Elucidating these relations is important both for understanding the physiological functions of endogenous genetic circuits and for designing robust synthetic systems. We describe a phenomenological study that reveals intrinsic constraints governing the allocation of resources toward protein synthesis and other aspects of cell growth. A theory incorporating these constraints can accurately predict how cell proliferation and geneexpression affect one another, quantitatively accounting for the effect of translation-inhibiting antibiotics on geneexpression and the effect of gratuitous protein expression on cell growth. The use of such empirical relations, analogous to phenomenological laws, may facilitate our understanding and manipulation of complex biological systems before underlying regulatory circuits are elucidated.

Full Text Available Cellobiohydrolases (EC 3.2.1.91 are important exo enzymes involved in cellulose hydrolysis alongside endoglucanases (EC 3.2.1.4 and β-glucosidases (EC 3.2.1.21. Heterologous cellobiohydrolase geneexpression under constitutive promoter control using Saccharomyces cerevisiae as host system is of great importance for a successful SSF process. From this point of view, the main objective of the work was to use Yeplac181 expression vector as a recipient for cellobiohdrolase - cbhB encoding geneexpression under the control of the actin promoter, in Saccharomyces cerevisiae. Two hybridvectors, YEplac-Actp and YEplac-Actp-CbhB, were generated usingEscherichia coli XLI Blue for the cloning experiments. Constitutive cbhB geneexpression was checked by proteine gel electrophoresis (SDS-PAGE after insertion of these constructs into Saccharomyces cerevisiae.

Full Text Available BACKGROUND: Our understanding of disease is increasingly informed by changes in geneexpression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue geneexpression compendium with corresponding human cross-species analysis. METHODOLOGY/PRINCIPAL FINDINGS: The Affymetrix platform was utilized to catalogue geneexpression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were identified for each tissue and functional enrichment analysis revealed themes consistent with known physio-anatomic functions for each organ. In addition, a comparison of orthologous geneexpression between matched canine and human normal tissues uncovered remarkable similarity. To demonstrate the utility of this dataset, novel canine gene annotations were established based on comparative analysis of dog and human tissue selective geneexpression and manual curation of canine probeset mapping. Public access, using infrastructure identical to that currently in use for human normal tissues, has been established and allows for additional comparisons across species. CONCLUSIONS/SIGNIFICANCE: These data advance our understanding of the canine genome through a comprehensive analysis of geneexpression in a diverse set of tissues, contributing to improved functional annotation that has been lacking. Importantly, it will be used to inform future studies of disease in the dog as a model for human translational research and provides a novel resource to the community at large.

The nitroreductase/5-(azaridin-1-yl)-2,4-dinitrobenzamide (NTR/CB1954) enzyme/prodrug system is considered as a promising candidate for anti-cancer strategies by gene-directed enzyme prodrug therapy (GDEPT) and has recently entered clinical trials. It requires the genetic modification of tumor cells to express the E. coli enzyme nitroreductase that bioactivates the prodrug CB1954 to a powerful cytotoxin. This metabolite causes apoptotic cell death by DNA interstrand crosslinking. Enhancing the enzymatic NTR activity for CB1954 should improve the therapeutical potential of this enzyme-prodrug combination in cancer gene therapy. We performed de novo synthesis of the bacterial nitroreductase gene adapting codon usage to mammalian preferences. The synthetic gene was investigated for its expression efficacy and ability to sensitize mammalian cells to CB1954 using western blotting analysis and cytotoxicity assays. In our study, we detected cytoplasmic protein aggregates by expressing GFP-tagged NTR in COS-7 cells, suggesting an impaired translation by divergent codon usage between prokaryotes and eukaryotes. Therefore, we generated a synthetic variant of the nitroreductase gene, called ntro, adapted for high-level expression in mammalian cells. A total of 144 silent base substitutions were made within the bacterial ntr gene to change its codon usage to mammalian preferences. The codon-optimized ntro either tagged to gfp or c-myc showed higher expression levels in mammalian cell lines. Furthermore, the ntro rendered several cell lines ten times more sensitive to the prodrug CB1954 and also resulted in an improved bystander effect. Our results show that codon optimization overcomes expression limitations of the bacterial ntr gene in mammalian cells, thereby improving the NTR/CB1954 system at translational level for cancer gene therapy in humans

The claudin (CLDN) genes encode a family of proteins important in tight junction formation and function. Recently, it has become apparent that CLDN geneexpression is frequently altered in several human cancers. However, the exact patterns of CLDN expression in various cancers is unknown, as only a limited number of CLDN genes have been investigated in a few tumors. We identified all the human CLDN genes from Genbank and we used the large public SAGE database to ascertain the geneexpression of all 21 CLDN in 266 normal and neoplastic tissues. Using real-time RT-PCR, we also surveyed a subset of 13 CLDN genes in 24 normal and 24 neoplastic tissues. We show that claudins represent a family of highly related proteins, with claudin-16, and -23 being the most different from the others. From in silico analysis and RT-PCR data, we find that most claudin genes appear decreased in cancer, while CLDN3, CLDN4, and CLDN7 are elevated in several malignancies such as those originating from the pancreas, bladder, thyroid, fallopian tubes, ovary, stomach, colon, breast, uterus, and the prostate. Interestingly, CLDN5 is highly expressed in vascular endothelial cells, providing a possible target for antiangiogenic therapy. CLDN18 might represent a biomarker for gastric cancer. Our study confirms previously known CLDN geneexpression patterns and identifies new ones, which may have applications in the detection, prognosis and therapy of several human cancers. In particular we identify several malignancies that express CLDN3 and CLDN4. These cancers may represent ideal candidates for a novel therapy being developed based on CPE, a toxin that specifically binds claudin-3 and claudin-4

Full Text Available Abstract Background The schistosome blood flukes are complex trematodes and cause a chronic parasitic disease of significant public health importance worldwide, schistosomiasis. Their life cycle is characterised by distinct parasitic and free-living phases involving mammalian and snail hosts and freshwater. Microarray analysis was used to profile developmental geneexpression in the Asian species, Schistosoma japonicum. Total RNAs were isolated from the three distinct environmental phases of the lifecycle – aquatic/snail (eggs, miracidia, sporocysts, cercariae, juvenile (lung schistosomula and paired but pre-egg laying adults and adult (paired, mature males and egg-producing females, both examined separately. Advanced analyses including ANOVA, principal component analysis, and hierarchal clustering provided a global synopsis of geneexpression relationships among the different developmental stages of the schistosome parasite. Results Geneexpression profiles were linked to the major environmental settings through which the developmental stages of the fluke have to adapt during the course of its life cycle. Gene ontologies of the differentially expressedgenes revealed a wide range of functions and processes. In addition, stage-specific, differentially expressedgenes were identified that were involved in numerous biological pathways and functions including calcium signalling, sphingolipid metabolism and parasite defence. Conclusion The findings provide a comprehensive database of geneexpression in an important human pathogen, including transcriptional changes in genes involved in evasion of the host immune response, nutrient acquisition, energy production, calcium signalling, sphingolipid metabolism, egg production and tegumental function during development. This resource should help facilitate the identification and prioritization of new anti-schistosome drug and vaccine targets for the control of schistosomiasis.

Background Quantitative PCR (qPCR) is a common method for quantifying mRNA expression. Given the heterogeneity present in tumor tissues, it is crucial to normalize target mRNA expression data using appropriate reference genes that are stably expressed under a variety of pathological and experimental

Authors explain that the radiation effect on biological system is stochastic along the law of physics, differing from chemical effect, using instances of Cs-137 gamma-ray (GR) and benzene (BZ) exposures to mice and of resultant comprehensive analyses of geneexpression. Single GR irradiation is done with Gamma Cell 40 (CSR) to C57BL/6 or C3H/He mouse at 0, 0.6 and 3 Gy. BE is given orally at 150 mg/kg/day for 5 days x 2 weeks. Bone marrow cells are sampled 1 month after the exposure. Comprehensive geneexpression is analyzed by Gene Chip Mouse Genome 430 2.0 Array (Affymetrix) and data are processed by programs like case normalization, statistics, network generation, functional analysis etc. GR irradiation brings about changes of geneexpression, which are classifiable in common genes variable commonly on the dose change and stochastic genes variable stochastically within each dose: e.g., with Welch-t-test, significant differences are between 0/3 Gy (dose-specific difference, 455 pbs (probe set), in stochastic 2113 pbs), 0/0.6 Gy (267 in 1284 pbs) and 0.6/3 Gy (532 pbs); and with one-way analysis of variation (ANOVA) and hierarchial/dendrographic analyses, 520 pbs are shown to involve the dose-dependent 226 and dose-specific 294 pbs. It is also shown that at 3 Gy, expression of common genes are rather suppressed, including those related to the proliferation/apoptosis of B/T cells, and of stochastic genes, related to cell division/signaling. Ven diagram of the common genes of above 520 pbs, stochastic 2113 pbs at 3 Gy and 1284 pbs at 0.6 Gy shows the overlapping genes 29, 2 and 4, respectively, indicating only 35 pbs are overlapping in total. Network analysis of changes by GR shows the rather high expression of genes around hub of cAMP response element binding protein (CREB) at 0.6 Gy, and rather variable expression around CREB hub/suppressed expression of kinesin hub at 3 Gy; in the network by BZ exposure, unchanged or low expression around p53 hub and suppression

Full Text Available Abstract Background Beta-adrenergic receptor agonists (BA induce skeletal muscle hypertrophy, yet specific mechanisms that lead to this effect are not well understood. The objective of this research was to identify novel genes and physiological pathways that potentially facilitate BA induced skeletal muscle growth. The Affymetrix platform was utilized to identify geneexpression changes in mouse skeletal muscle 24 hours and 10 days after administration of the BA clenbuterol. Results Administration of clenbuterol stimulated anabolic activity, as indicated by decreased blood urea nitrogen (BUN; P P Conclusion Global evaluation of geneexpression after administration of clenbuterol identified changes in geneexpression and overrepresented functional categories of genes that may regulate BA-induced muscle hypertrophy. Changes in mRNA abundance of multiple genes associated with myogenic differentiation may indicate an important effect of BA on proliferation, differentiation, and/or recruitment of satellite cells into muscle fibers to promote muscle hypertrophy. Increased mRNA abundance of genes involved in the initiation of translation suggests that increased levels of protein synthesis often associated with BA administration may result from a general up-regulation of translational initiators. Additionally, numerous other genes and physiological pathways were identified that will be important targets for further investigations of the hypertrophic effect of BA on skeletal muscle.

Purpose: To extend knowledge on the mechanisms and pathways involved in maintenance of radiation-induced fibrosis (RIF) by performing geneexpression profiling of whole blood from breast cancer (BC) survivors with and without fibrosis 3-7 years after end of radiotherapy treatment. Methods and Materials: Geneexpression profiles from blood were obtained for 254 BC survivors derived from a cohort of survivors, treated with adjuvant radiotherapy for breast cancer 3-7 years earlier. Analyses of transcriptional differences in blood geneexpression between BC survivors with fibrosis (n = 31) and BC survivors without fibrosis (n = 223) were performed using R version 2.8.0 and tools from the Bioconductor project. Gene sets extracted through a literature search on fibrosis and breast cancer were subsequently used in gene set enrichment analysis. Results: Substantial differences in blood geneexpression between BC survivors with and without fibrosis were observed, and 87 differentially expressedgenes were identified through linear analysis. Transforming growth factor-β1 signaling was identified as the most significant gene set, showing a down-regulation of most of the core genes, together with up-regulation of a transcriptional activator of the inhibitor of fibrinolysis, Plasminogen activator inhibitor 1 in the BC survivors with fibrosis. Conclusion: Transforming growth factor-β1 signaling was found down-regulated during the maintenance phase of fibrosis as opposed to the up-regulation reported during the early, initiating phase of fibrosis. Hence, once the fibrotic tissue has developed, the maintenance phase might rather involve a deregulation of fibrinolysis and altered degradation of extracellular matrix components.

Purpose: In a large-scale radiologic emergency, estimates of exposure doses and radiation injury would be required for individuals without physical dosimeters. Current methods are inadequate for the task, so we are developing geneexpression profiles for radiation biodosimetry. This approach could provide both an estimate of physical radiation dose and an indication of the extent of individual injury or future risk. Methods and Materials: We used whole genome microarray expression profiling as a discovery platform to identify genes with the potential to predict radiation dose across an exposure range relevant for medical decision making in a radiologic emergency. Human peripheral blood from 10 healthy donors was irradiated ex vivo, and global geneexpression was measured both 6 and 24 h after exposure. Results: A 74-gene signature was identified that distinguishes between four radiation doses (0.5, 2, 5, and 8 Gy) and controls. More than one third of these genes are regulated by TP53. A nearest centroid classifier using these same 74 genes correctly predicted 98% of samples taken either 6 h or 24 h after treatment as unexposed, exposed to 0.5, 2, or ≥5 Gy. Expression patterns of five genes (CDKN1A, FDXR, SESN1, BBC3, and PHPT1) from this signature were also confirmed by real-time polymerase chain reaction. Conclusion: The ability of a single gene set to predict radiation dose throughout a window of time without need for individual pre-exposure controls represents an important advance in the development of geneexpression for biodosimetry

Full Text Available Previous expression quantitative trait loci (eQTL studies have performed genetic association studies for geneexpression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of geneexpression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining geneexpression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs. The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5, the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and geneexpression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus.

Previous expression quantitative trait loci (eQTL) studies have performed genetic association studies for geneexpression, but most of these studies examined lymphoblastoid cell lines from non-diseased individuals. We examined the genetics of geneexpression in a relevant disease tissue from chronic obstructive pulmonary disease (COPD) patients to identify functional effects of known susceptibility genes and to find novel disease genes. By combining geneexpression profiling on induced sputum samples from 131 COPD cases from the ECLIPSE Study with genomewide single nucleotide polymorphism (SNP) data, we found 4315 significant cis-eQTL SNP-probe set associations (3309 unique SNPs). The 3309 SNPs were tested for association with COPD in a genomewide association study (GWAS) dataset, which included 2940 COPD cases and 1380 controls. Adjusting for 3309 tests (p<1.5e-5), the two SNPs which were significantly associated with COPD were located in two separate genes in a known COPD locus on chromosome 15: CHRNA5 and IREB2. Detailed analysis of chromosome 15 demonstrated additional eQTLs for IREB2 mapping to that gene. eQTL SNPs for CHRNA5 mapped to multiple linkage disequilibrium (LD) bins. The eQTLs for IREB2 and CHRNA5 were not in LD. Seventy-four additional eQTL SNPs were associated with COPD at p<0.01. These were genotyped in two COPD populations, finding replicated associations with a SNP in PSORS1C1, in the HLA-C region on chromosome 6. Integrative analysis of GWAS and geneexpression data from relevant tissue from diseased subjects has located potential functional variants in two known COPD genes and has identified a novel COPD susceptibility locus. PMID:21949713

Full Text Available Rhinovirus (RV is the most prevalent human respiratory virus and is responsible for at least half of all common colds. RV infections may result in a broad spectrum of effects that range from asymptomatic infections to severe lower respiratory illnesses. The basis for inter-individual variation in the response to RV infection is not well understood. In this study, we explored whether host genetic variation is associated with variation in geneexpression response to RV infections between individuals. To do so, we obtained genome-wide genotype and geneexpression data in uninfected and RV-infected peripheral blood mononuclear cells (PBMCs from 98 individuals. We mapped local and distant genetic variation that is associated with inter-individual differences in geneexpression levels (eQTLs in both uninfected and RV-infected cells. We focused specifically on response eQTLs (reQTLs, namely, genetic associations with inter-individual variation in geneexpression response to RV infection. We identified local reQTLs for 38 genes, including genes with known functions in viral response (UBA7, OAS1, IRF5 and genes that have been associated with immune and RV-related diseases (e.g., ITGA2, MSR1, GSTM3. The putative regulatory regions of genes with reQTLs were enriched for binding sites of virus-activated STAT2, highlighting the role of condition-specific transcription factors in genotype-by-environment interactions. Overall, we suggest that the 38 loci associated with inter-individual variation in geneexpression response to RV-infection represent promising candidates for affecting immune and RV-related respiratory diseases.

Rhinovirus (RV) is the most prevalent human respiratory virus and is responsible for at least half of all common colds. RV infections may result in a broad spectrum of effects that range from asymptomatic infections to severe lower respiratory illnesses. The basis for inter-individual variation in the response to RV infection is not well understood. In this study, we explored whether host genetic variation is associated with variation in geneexpression response to RV infections between individuals. To do so, we obtained genome-wide genotype and geneexpression data in uninfected and RV-infected peripheral blood mononuclear cells (PBMCs) from 98 individuals. We mapped local and distant genetic variation that is associated with inter-individual differences in geneexpression levels (eQTLs) in both uninfected and RV-infected cells. We focused specifically on response eQTLs (reQTLs), namely, genetic associations with inter-individual variation in geneexpression response to RV infection. We identified local reQTLs for 38 genes, including genes with known functions in viral response (UBA7, OAS1, IRF5) and genes that have been associated with immune and RV-related diseases (e.g., ITGA2, MSR1, GSTM3). The putative regulatory regions of genes with reQTLs were enriched for binding sites of virus-activated STAT2, highlighting the role of condition-specific transcription factors in genotype-by-environment interactions. Overall, we suggest that the 38 loci associated with inter-individual variation in geneexpression response to RV-infection represent promising candidates for affecting immune and RV-related respiratory diseases.

Gene flow is a common phenomenon even in self-pollinated plant species. With the advent of genetically modified plants this subject has become of the utmost importance due to the need for controlling the spread of transgenes. This study was conducted to determine the occurrence and intensity of outcrossing in transgenic common beans. In order to evaluate the outcross rates, four experiments were conducted in Santo Antonio de Goiás (GO, Brazil) and one in Londrina (PR, Brazil), using transgenic cultivars resistant to the herbicide glufosinate ammonium and their conventional counterparts as recipients of the transgene. Experiments with cv. Olathe Pinto and the transgenic line Olathe M1/4 were conducted in a completely randomized design with ten replications for three years in one location, whereas the experiments with cv. Pérola and the transgenic line Pérola M1/4 were conducted at two locations for one year, with the transgenic cultivar surrounded on all sides by the conventional counterpart. The outcross occurred at a negligible rate of 0.00741% in cv. Pérola, while none was observed (0.0%) in cv. Olathe Pinto. The frequency of gene flow was cultivar dependent and most of the observed outcross was within 2.5 m from the edge of the pollen source. Index terms: Phaseolus vulgaris, outcross, glufosinate ammonium.

UBX (ubiquitin regulatory X)-containing proteins belong to an evolutionary conserved protein family and determine the specificity of p97/VCP/Cdc48p function by binding as its adaptors. Caenorhabditis elegans was found to possess six UBX-containing proteins, named UBXN-1 to -6. However, no general or specific function of them has been revealed. During the course of understanding not only their function but also specified function of p97, we investigated spatial and temporal expression patterns of six ubxn genes in this study. Transcript analyses showed that the expression pattern of each ubxn gene was different throughout worm's development and may show potential developmental dynamics in their function, especially ubxn-5 was expressed specifically in the spermatogenic germline, suggesting a crucial role in spermatogenesis. In addition, as ubxn-4 expression was induced by ER stress, it would function as an ERAD factor in C. elegans. In vivo expression analysis by using GFP translational fusion constructs revealed that six ubxn genes show distinct expression patterns. These results altogether demonstrate that the expression of all six ubxn genes of C. elegans is differently regulated

Full Text Available Aim This study analyze the MnSOD geneexpression as endogenous antioxidant in human glioma cells compared with leucocyte cells as control.Methods MnSOD geneexpression of 20 glioma patients was analyzed by measuring the relative expression of mRNA and enzyme activity of MnSOD in brain and leucocyte cells. The relative expression of mRNA MnSOD was determined by using quantitative Real Time RT-PCR and the enzyme activity of MnSOD using biochemical kit assay (xantine oxidase inhibition. Statistic analysis for mRNA and enzyme activity of MnSOD was performed using Kruskal Wallis test.Results mRNA of MnSOD in glioma cells of 70% sample was 0.015–0.627 lower, 10% was 1.002-1.059 and 20% was 1.409-6.915 higher than in leucocyte cells. Also the specific activity of MnSOD enzyme in glioma cells of 80% sample showed 0,064-0,506 lower and 20% sample was 1.249-2.718 higher than in leucocyte cells.Conclusion MnSOD geneexpression in human glioma cells are significantly lower than its expression in leucocytes cells. (Med J Indones 2010; 19:21-5Keywords : MnSOD, glioma, geneexpression

Background For centuries roses have been selected based on a number of traits. Little information exists on the genetic and molecular basis that contributes to these traits, mainly because information on expressedgenes for this economically important ornamental plant is scarce. Results Here, we used a combination of Illumina and 454 sequencing technologies to generate information on Rosa sp. transcripts using RNA from various tissues and in response to biotic and abiotic stresses. A total of 80714 transcript clusters were identified and 76611 peptides have been predicted among which 20997 have been clustered into 13900 protein families. BLASTp hits in closely related Rosaceae species revealed that about half of the predicted peptides in the strawberry and peach genomes have orthologs in Rosa dataset. Digital expression was obtained using RNA samples from organs at different development stages and under different stress conditions. qPCR validated the digital expression data for a selection of 23 genes with high or low expression levels. Comparative geneexpression analyses between the different tissues and organs allowed the identification of clusters that are highly enriched in given tissues or under particular conditions, demonstrating the usefulness of the digital geneexpression analysis. A web interface ROSAseq was created that allows data interrogation by BLAST, subsequent analysis of DNA clusters and access to thorough transcript annotation including best BLAST matches on Fragaria vesca, Prunus persica and Arabidopsis. The rose peptides dataset was used to create the ROSAcyc resource pathway database that allows access to the putative genes and enzymatic pathways. Conclusions The study provides useful information on Rosa expressedgenes, with thorough annotation and an overview of expression patterns for transcripts with good accuracy. PMID:23164410

Clustered regularly interspaced short palindromic repeats (CRISPR) loci and their associated cas (CRISPR-associated) genes provide adaptive immunity against viruses (phages) and other mobile genetic elements in bacteria and archaea. While most of the early work has largely been dominated by examples of CRISPR-Cas systems directing the cleavage of phage or plasmid DNA, recent studies have revealed a more complex landscape where CRISPR-Cas loci might be involved in gene regulation. In this review, we summarize the role of these loci in the regulation of geneexpression as well as the recent development of synthetic gene regulation using engineered CRISPR-Cas systems. PMID:24273648

OBJECTIVE: Differential geneexpression in CD177+ and CD177- neutrophils was investigated, in order to detect possible differences in neutrophil function which could be related to the pathogenesis of ANCA-associated Vasculitides (AAV). METHODS: Neutrophils were isolated from healthy controls (HC......) with high, negative or bimodal CD177 expression, and sorted into CD177+ and CD177- subpopulations. Total RNA was screened for expression of 24,000 probes with Illumina Ref-8 Beadchips. Genes showing differential expression between CD177+ and CD177- subsets in microarray analysis were re-assessed using...... quantitative-PCR. CD177 expression on neutrophil precursors in bone marrow was analyzed using quantitative PCR and flowcytometry. RESULTS: The proportion of CD177+ cells increased during neutrophil maturation in bone marrow. Fold change analysis of geneexpression profile of sorted CD177+ and CD177...

Full Text Available Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing geneexpression data in cross-sectional studies. The time-course gene set analysis (TcGSA introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estimates. It allows to use all available repeated measurements while dealing with unbalanced data due to missing at random (MAR measurements. TcGSA is a hypothesis driven method that identifies a priori defined gene sets with significant expression variations over time, taking into account the potential heterogeneity of expression within gene sets. When biological conditions are compared, the method indicates if the time patterns of gene sets significantly differ according to these conditions. The interest of the method is illustrated by its application to two real life datasets: an HIV therapeutic vaccine trial (DALIA-1 trial, and data from a recent study on influenza and pneumococcal vaccines. In the DALIA-1 trial TcGSA revealed a significant change in geneexpression over time within 69 gene sets during vaccination, while a standard univariate individual gene analysis corrected for multiple testing as well as a standard a Gene Set Enrichment Analysis (GSEA for time series both failed to detect any significant pattern change over time. When applied to the second illustrative data set, TcGSA allowed the identification of 4 gene sets finally found to be linked with the influenza vaccine too although they were found to be associated to the pneumococcal vaccine only in previous analyses. In our simulation study TcGSA exhibits good statistical properties, and an increased power compared to other approaches for analyzing time-course expression patterns of gene sets. The method is made available for the community through an R package.

Full Text Available Abstract Background Clustering is a widely used technique for analysis of geneexpression data. Most clustering methods group genes based on the distances, while few methods group genes according to the similarities of the distributions of the geneexpression levels. Furthermore, as the biological annotation resources accumulated, an increasing number of genes have been annotated into functional categories. As a result, evaluating the performance of clustering methods in terms of the functional consistency of the resulting clusters is of great interest. Results In this paper, we proposed the WDCM (Weibull Distribution-based Clustering Method, a robust approach for clustering geneexpression data, in which the geneexpressions of individual genes are considered as the random variables following unique Weibull distributions. Our WDCM is based on the concept that the genes with similar expression profiles have similar distribution parameters, and thus the genes are clustered via the Weibull distribution parameters. We used the WDCM to cluster three cancer geneexpression data sets from the lung cancer, B-cell follicular lymphoma and bladder carcinoma and obtained well-clustered results. We compared the performance of WDCM with k-means and Self Organizing Map (SOM using functional annotation information given by the Gene Ontology (GO. The results showed that the functional annotation ratios of WDCM are higher than those of the other methods. We also utilized the external measure Adjusted Rand Index to validate the performance of the WDCM. The comparative results demonstrate that the WDCM provides the better clustering performance compared to k-means and SOM algorithms. The merit of the proposed WDCM is that it can be applied to cluster incomplete geneexpression data without imputing the missing values. Moreover, the robustness of WDCM is also evaluated on the incomplete data sets. Conclusions The results demonstrate that our WDCM produces clusters

Full Text Available Background: Microarray technology has become highly valuable for identifying complex global changes in geneexpression patterns. The assignment of functional information to these complex patterns remains a challenging task in effectively interpreting data and correlating results from across experiments, projects and laboratories. Methods which allow the rapid and robust evaluation of multiple functional hypotheses increase the power of individual researchers to data mine geneexpression data more efficiently.Results: We have developed (gene set matrix analysis GSMA as a useful method for the rapid testing of group-wise up- or downregulation of geneexpression simultaneously for multiple lists of genes (gene sets against entire distributions of geneexpression changes (datasets for single or multiple experiments. The utility of GSMA lies in its flexibility to rapidly poll gene sets related by known biological function or as designated solely by the end-user against large numbers of datasets simultaneously.Conclusions: GSMA provides a simple and straightforward method for hypothesis testing in which genes are tested by groups across multiple datasets for patterns of expression enrichment.

Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published geneexpression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressedgenes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

We have previously shown a higher level of HIV-1 replication and geneexpression in neonatal (cord) blood mononuclear cells (CBMC) compared with adult blood cells (PBMC), which could be due to differential expression of host factors. We performed the geneexpression profile of CBMC and PBMC and found that 8013 genes were expressed at higher levels in CBMC than PBMC and 8028 genes in PBMC than CBMC, including 1181 and 1414 genes upregulated after HIV-1 infection in CBMC and PBMC, respectively. Several transcription factors (NF-κB, E2F, HAT-1, TFIIE, Cdk9, Cyclin T1), signal transducers (STAT3, STAT5A) and cytokines (IL-1β, IL-6, IL-10) were upregulated in CBMC than PBMC, which are known to influence HIV-1 replication. In addition, a repressor of HIV-1 transcription, YY1, was down regulated in CBMC than PBMC and several matrix metalloproteinase (MMP-7, -12, -14) were significantly upregulated in HIV-1 infected CBMC than PBMC. Furthermore, we show that CBMC nuclear extracts interacted with a higher extent to HIV-1 LTR cis-acting sequences, including NF-κB, NFAT, AP1 and NF-IL6 compared with PBMC nuclear extracts and retroviral based short hairpin RNA (shRNA) for STAT3 and IL-6 down regulated their own and HIV-1 geneexpression, signifying that these factors influenced differential HIV-1 geneexpression in CBMC than PBMC.

A combined packing and assembly method that efficiently packs ribonucleic acid (RNA) into virus like particles (VLPs) has been developed. The VLPs can spontaneously assemble and load RNA in vivo, efficiently packaging specifically designed RNAs at high densities and with high purity. In some embodiments the RNA is capable of interference activity, or is a precursor of a RNA capable of causing interference activity. Compositions and methods for the efficient expression, production and purification of VLP-RNAs are provided. VLP-RNAs can be used for the storage of RNA for long periods, and provide the ability to deliver RNA in stable form that is readily taken up by cells.

Full Text Available This paper discusses mathematical and statistical aspects in analysis methods applied to microarray geneexpressions. We focus on pattern recognition to extract informative features embedded in the data for prediction of phenotypes. It has been pointed out that there are severely difficult problems due to the unbalance in the number of observed genes compared with the number of observed subjects. We make a reanalysis of microarray geneexpression published data to detect many other gene sets with almost the same performance. We conclude in the current stage that it is not possible to extract only informative genes with high performance in the all observed genes. We investigate the reason why this difficulty still exists even though there are actively proposed analysis methods and learning algorithms in statistical machine learning approaches. We focus on the mutual coherence or the absolute value of the Pearson correlations between two genes and describe the distributions of the correlation for the selected set of genes and the total set. We show that the problem of finding informative genes in high dimensional data is ill-posed and that the difficulty is closely related with the mutual coherence.

Full Text Available Abstract Background Cell-specific expression of the gene that encodes brain-derived neurotrophic factor (BDNF is required for the normal development of peripheral sensory neurons and efficient synaptic transmission in the mature central and peripheral nervous system. The control of BDNF geneexpression involves multiple tissue and cell-specific promoters that are differentially regulated. The molecular mechanisms that are responsible for tissue and cell-specific expression of these promoters are still incompletely understood. Results The cloning and analysis of three additional zebrafish (Danio rerio BDNF gene exons and two associated promoters, is reported. Among them are two exons that generate a novel tripartite mature transcript. The exons were located on the transcription unit, whose overall organization was determined by cloning, Southern blot hybridization and sequence analysis, and compared with the pufferfish (Fugu rubripes and mammalian BDNF loci, revealing a conserved but more compact organization. Structural and functional analysis of the exons, their adjacent promoters and 5' flanks, showed that they are expressed cell-specifically. The promoter associated with the 5' exon of the tripartite transcript is GC-rich, TATA-less and the 5' flank adjacent to it contains multiple Sp1, Mef2, and AP1 elements. A fusion gene containing the promoter and 1.5 KB of 5' flank is directed exclusively to skeletal muscle of transiently transfected embryos. The second promoter, whose associated 5' exon contains a 25-nucleotide segment of identity with a mammalian BDNF gene exon, was transiently expressed in yolk of the early embryo. RT-PCR analysis of total RNA from whole juvenile fish and adult female skeletal muscle revealed tissue-specific expression of the 5' exons but the novel exon could not be detected even after two rounds of nested PCR. Conclusion The zebrafish BDNF gene is as complex as the mammalian gene yet much more compact. Its exons are

Full Text Available Reverse transcription-qPCR (RT-qPCR has become a popular method for geneexpression studies. Its results require data normalization by housekeeping genes. No single gene is proved to be stably expressed under all experimental conditions. Therefore, systematic evaluation of reference genes is necessary. With the aim to identify optimum reference genes for RT-qPCR analysis of geneexpression in different tissues of Panax ginseng and the seedlings grown under heat stress, we investigated the expression stability of eight candidate reference genes, including elongation factor 1-beta (EF1-β, elongation factor 1-gamma (EF1-γ, eukaryotic translation initiation factor 3G (IF3G, eukaryotic translation initiation factor 3B (IF3B, actin (ACT, actin11 (ACT11, glyceraldehyde-3-phosphate dehydrogenase (GAPDH and cyclophilin ABH-like protein (CYC, using four widely used computational programs: geNorm, Normfinder, BestKeeper, and the comparative ΔCt method. The results were then integrated using the web-based tool RefFinder. As a result, EF1-γ, IF3G and EF1-β were the three most stable genes in different tissues of P. ginseng, while IF3G, ACT11 and GAPDH were the top three-ranked genes in seedlings treated with heat. Using three better reference genes alone or in combination as internal control, we examined the expression profiles of MAR, a multiple function-associated mRNA-like non-coding RNA (mlncRNA in P. ginseng. Taken together, we recommended EF1-γ/IF3G and IF3G/ACT11 as the suitable pair of reference genes for RT-qPCR analysis of geneexpression in different tissues of P. ginseng and the seedlings grown under heat stress, respectively. The results serve as a foundation for future studies on P. ginseng functional genomics.

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from GeneExpression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressedgenes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressedgene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput geneexpression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from geneexpression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

Auxin oxidation has been reported to play a critical role in the initiation of pear fruit ripening and a tomato fruit peroxidase (POD) has been shown to have IAA-oxidase activity. However, little is known about changes in the expression of POD mRNA in tomato fruit development. They are investigating the expression of POD mRNA during tomato fruit maturation. Fruit pericarp tissues from six stages of fruit development and ripening (immature green, mature green, breaker, turning, ripe, and red ripe fruits) were used to extract poly (A) + RNAs. These RNAs were translated in vitro in a rabbit reticulocyte lysate system using L- 35 S-methionine. The 35 S-labeled products were immunoprecipitated with POD antibodies to determine the relative proportions of POD mRNA. High levels of POD mRNA were present in immature green and mature green pericarp, but declined greatly by the turning stage of fruit ripening. In addition, the distribution of POD mRNA on free vs bound polyribosomes will be presented, as well as the presence or absence of POD mRNA in other tomato tissues